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1Z0-450 Oracle Application Express 3.2-(R) Developing Web Applications

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Test appellation : Oracle Application Express 3.2-(R) Developing Web Applications
Vendor appellation : Oracle
: 49 existent Questions

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Oracle Oracle Application Express 3.2-(R)

NetSuite CEO Evan Goldberg: Oracle possession is symbiotic | killexams.com existent Questions and Pass4sure dumps

Evan Goldberg, founder and chief executive officer of NetSuite, contends that the application-as-a-service traffic has amplified itself when you deem that being got through Oracle in 2016.

Arguably, the enterprise did possess “made at Oracle” stamped on it from the starting. Oracle founder Larry Ellison turned into an colossal shareholder, and was a mentor to Goldberg.

He still is. Goldberg moreover confirms that Ellison is as comical in precise lifestyles as he's on stage. “He has an excellent experience of humour,” he says. “loads of very shrewd people do. he's self-deprecating, and he can note the absurdity in lots of issues.”

Goldberg says Ellison’s energetic involvement in the entire expertise aspects of Oracle might possess approach as surprise to a few NetSuite personnel, but no longer to him. “Very soon after the acquisition, Larry got here and spoke to their entire R&D product evolution enterprise,” he says. “He knew precisely what they did, how they did it, and what their cost proposition was. He begun the enterprise – I suppose he gets it.”

Goldberg at the start joined Oracle straight from Harvard in 1987 when it had about 900 employees.

NetSuite, which he centered in 1998, was prior to now a cloud applications company referred to as NetLedger. He remembers: “We began a yoke of months before salesforce.com. They had a focus on a complete enterprise management suite for small and transforming into, and mid-market organizations. They moved up the ladder as they grew out the product, but they stored their eyes on that prize throughout the 18 years they possess been an unbiased company, getting immediate to $1bn in annual income.

“Oracle is investing very heavily in NetSuite – in R&D, however additionally in increasing internationally”

Evan Goldberg, NetSuite

“but then Oracle purchased NetSuite to finished their cloud portfolio for ERP [enterprise resource planning] and enterprise administration SaaS purposes for gigantic organizations. They possess been now not as concentrated on agencies that possess been going from the storage to IPO [initial public offering], which has been their focus. nonetheless it become Larry’s imaginative and prescient to carry – at first accounting – application over the net [in 1998]. They possess been always cousin corporations, and for me it’s a coming again. I spent the primary eight years of my profession at Oracle.”

here is an edited extract of an interview Goldberg did with computer Weekly earlier this month.

How are issues distinctive for NetSuite as a section of Oracle?

Goldberg: Oracle is investing very closely in NetSuite. In R&D, however additionally in expanding internationally – the Nordics, Benelux, France – whereas previously, their overseas seat of attention become very tons UK. but that additionally merits UK valued clientele as they expand internationally, making sure NetSuite works, getting every thing arrogate for whichever locality, when it comes to language, customs, tax, impregnate options, delivery, and so forth.

It’s offered us with a stage of focal point we’ve not had in a long time. probably the most first issues that [Oracle CEO] sign Hurd said after the acquisition became that NetSuite would exist out there for ever.

And below the covers, they will be supplying a brand-new analytics engine, with actual-time facts, and that's the kindly of aspect they are able to now do. one of the crucial motives that I stayed became to note through some of these deep investments in the platform to acquire NetSuite more bendy, extra verticalised, in order that it's suitable for every individual company.

in case you deem of your market, is it very a lot small to medium, however quick-growing to be – as adversarial to just SME?

Goldberg: one of the vital issues they now possess done at Oracle is carry SuiteSuccess editions. That’s how their valued clientele purchase NetSuite – it's more than only a application software, it is the whole technique in which they interject it into their lifecycle.

They may not be quickly-starting to be, but usually they are organizations that are geographically allotted in a number of countries. I’d mumble it’s companies that possess outgrown their initial fiscal software, no matter if that’s QuickBooks in the US or Sage within the UK, as soon as their traffic has turn into greater advanced.

That’s why I each and every started NetSuite within the first region, as a result of I could see, from a further startup, I didn’t possess the relaxation that might tie everything together in the traffic and permit me to note every thing happening in my enterprise in a dashboard.

however, for example, American express spun off its enterprise trip company GBT [Global traffic Travel] and that runs on NetSuite. They finish possess corporations which possess grown up with us from a whole lot of millions of greenbacks to 1000000000 plus. Now there may well be agencies where complexity goes to such a even that Oracle cloud software is a rational destination, but is rather rare. we've been in a position to scale.

within the context of a more generic shift to the cloud, what finish you note as NetSuite’s enduring cost proposition?

Goldberg: at the start, they had been selling the each time, anyplace aspect of the cloud – even though it wasn’t known as the cloud then; it was ASP [application service provider] or internet applications. And at the birth they bumped into resistance. You had [Salesforce CEO] Marc Benioff selling software-as-a-service income people. but finance people are with the aid of nature greater conservative, and they had to mumble to them: “you're reluctant to do your finance guidance in the cloud, yet your sales contact counsel is there.” and that i can’t negate Salesforce.com’s hype created a wave for us.

but you’re right. The total narrative has flipped. Now, it’s “why would I need my assistance to be on my computers?”. So it has to be about more than just the cloud for us. What they possess approach back to is the other key component of their strategy, which is to convey a single utility throughout not simply fiscal, not just ERP, but commerce, and HR, with SuitePeople.

The most fulfilling engage is your entire tips in one area, with a single UI for your entire users. it is what we’re hanging their hat on, and for plenty of corporations. they now possess grotesque charities using us, like Compassion in World Farming in the UK. These fast-turning out to be charities need the same visibility into their traffic as for-earnings agencies.

What are the advantages of Oracle’s self sustaining database and cloud obligate for NetSuite, seeing that your shoppers received’t be employing lots of DBAs [database administrators] anyway?

Goldberg: they are affecting NetSuite to the Oracle Cloud Infrastructure (OCI). as an instance, they could be delivering to German purchasers from a German datacentre over the OCI. And the Oracle Cloud Infrastructure engage is an identical merits for us as every other business. they will focal point on providing their carrier and let them scrutinize after the nuts and bolts of the infrastructure, and how it receives on to the cyber web.

How finish you note the mid-market traffic applications market altering? SAP has made a colossal turn to the client with C/4 Hana, Microsoft Dynamics is a serious player, you possess Infor carrying on with to improve in the cloud, and Anaplan with fiscal planning within the cloud. What’s your examine?

Goldberg: You be vigilant of, it has been pretty static in their market segment. No selection is their greatest competition. They don’t note SAP, Microsoft has been very sluggish to enhance cloud-based models of mid-market purposes. So it’s a green sphere with a smorgasbord of local solutions internationally, and they are providing something this uniform each and every over the world.


AI and ML latest news: NewRelic acquires startup SignifAI to bring 'utilized intelligence' to DevOps | killexams.com existent Questions and Pass4sure dumps

NewRelic, the cloud-based mostly utility analytics firm, has brought machine studying to its armoury in the shape of SignifAI, an Israeli-US startup concentrated on experience intelligence - or sorting sign from uproar in the fast-relocating box of DevOps.

SignifAI, in keeping with its white paper, is a 'SaaS-based mostly correlation engine that leverages AI and computer researching to rupture down the records silos present in complex traffic IT environments.'

It integrates by way of APIs to around 60 conventional monitoring and collaboration outfit including Splunk, AppDynamics, Slack, AWS, Nagios - and NewRelic itself - and guarantees to assist developers establish the foundation reason for mistakes by sifting via routine, logs, time-sequence statistics and infrastructure indicators, rating and outputting probably the most probably factors to a person console or during the monitoring device. users can additionally coach the mannequin to multiply the accuracy of the correlations.

AIOps is a comparatively recent addition to the blizzard of AI and DevOps-related phrases. It refers back to the consume of computer studying to analyse information amassed from a variety of IT operations outfit and contraptions as a way to spot and react to issues in True time.

within the business's weblog, NewRelic's chief product officer Jim Gochee comes down in favour of  the term ‘utilized intelligence' to clarify the utility of desktop gaining information of to the software evolution system.

"We decided to consume the time age 'applied Intelligence' to report their philosophy and approach to bringing ersatz intelligence (AI) / machine researching (ML) to their house. They selected 'applied Intelligence' to remind ourselves to normally ponder the particular person words and their meanings, with the goal of retaining us on the privilege track to bring definitely significant client cost with their AI efforts," he writes.

04/02/2019 Heathrow trials AI outfit for touchdown planes in contemptible climate

In unhealthy climate, visibility from Heathrow's 87-metre tall handle tower will moreover be enormously reduced as low clouds obscure the views of the runways below.

When this happens, air traffic controllers need to weigh on radar to be sure that a plane that has simply landed has cleared the runway, and a margin of error must be built in for protection. This causes delays and backlogs and a 20 per cent loss of landing skill, in line with Airport World.

here's a neighborhood where AI - together with ultra HD 4K cameras - can support, believes air traffic manage service NATS. The supplier has begun a trial the usage of 20 such cameras do in within the tower together with a desktop learning device called Aimee which has been developed by using Canadian vendor Searidge applied sciences. an identical trial is underway at Singapore's Changi Airport.

as soon as informed, Aimee should still be able to song the aircraft from the time they land until they're limpid of the runway, even when the cameras' photographs are complicated to interpret by using the human eye. it will then alert the air traffic controller who will acquire the remaining selection on even if to limpid the subsequent arriving flight for touchdown. As such, Aimee is very a splendid deal an assist to human determination making instead of being an self reliant manage system. 

The behaviour of fifty,000 arriving aircraft should be studied over the subsequent one year to note how the gadget responds to actual-world cases.

AI is likely to play an more and more faultfinding office within the management of air site visitors in the future, together with for Heathrow's planned third runway, talked about Heathrow's operations director, Kathryn Leahy.

"we are going to be protecting a particular eye on this trial, because the know-how may possess a major role as they do together for the accelerated airport. they will watch how AI and digital towers may be used to panoply screen each and every three of the increased airport's runways in future," she noted.

The outcomes of the trial should be introduced to be introduced to the uk Civil Aviation Authority next March.

28/01/2019 Amazon open-sources its SageMaker Neo machine discovering optimisation software

Raspberry Pi Zero

Amazon has open-sourced SageMaker Neo, its application for practising computing device learning models and optimising the style they elope on different types of instruments.

SageMaker Neo is designed to ensure that ML models elope as efficiently as possible on loads of machines and environments. not like the practicing stage, during which models are frequently honed on excessive-powered machines, for the inference stage, where the model makes predictions in accordance with recent data, it can be running on plenty lowlier gadgets.

The environment can possess a great sequel on the age of time it takes for a mannequin to deduce a outcome and on the variety of such calculations that can be elope in parallel. On region contraptions within the IoT - a single board computer like a Raspberry Pi for illustration - latency and constrained concurrency can be extreme impediments. ML models are far from gadget-agnostic.

Most instruments may moreover be optimised to velocity up the inference method, but this frequently involves a unprejudiced small bit of sheperd tinkering and trial and blunder. The usual SageMaker changed into a mannequin training framework, but SageMaker Neo, brought ultimate November, combines that with an optimisation stage, taking the absolutely trained mannequin and generating an executable it really is particular to the goal machine - be that a GPU or a Pi.

"Amazon SageMaker Neo instantly optimises machine getting to know models to perform at as much as twice the pace without a loss in accuracy. You start with a machine gaining information of model built using MXNet, TensorFlow, PyTorch, or XGBoost and knowledgeable using Amazon SageMaker. then you definitely select your target hardware platform from Intel, Nvidia, or Arm. With a single click, SageMaker Neo will then assemble the educated model into an executable," the company says on its site, including that the compiler makes consume of neural networking suggestions to analyse the goal platform so that optimisations can moreover be utilized.

The Neo-AI venture is obtainable on Github below the Apache software License, enabling developers to tailor the code to recede well with their personal needs.

other cloud establishments, including Microsoft and Google, are additionally working on applying AI to the ‘intelligent area'.

07/01/2019 Huawei broadcasts 'optimum performance ARM-based CPU' geared toward AI workloads

Huawei has announced what it claims is the realm's most suitable performing ARM-primarily based processor.

Unveiled on Sunday, the Kunpeng 920 is intention-developed for AI workloads that involve processing massive volumes of facts utilising distributed storage.

In SPECint benchmarking tests, the Kunpeng 920 scored greater than 930, or basically 25 per cent larger than the trade benchmark, whereas the usage of 30 per cent less vigour than competitors, Huawei claims.

The Huawei-designed processor is manufactured on a 7-nanometer system in keeping with the ARM architecture. It has sixty four cores with clock velocity 2.6GHz and 8-channel DDR4 memory.

The better efficiency is basically as a result of optimised branch prediction algorithms and an extended number of OP contraptions, along with an more desirable reminiscence subsystem structure, in response to the enterprise.

"nowadays, with Kunpeng 920, they are getting into an era of diverse computing embodied by distinct cores and heterogeneity. Huawei has invested patiently and intensively in computing innovation to continuously acquire breakthroughs. they are able to work with their clients and companions to build a totally linked, shrewd world," pointed out William Xu, Huawei's chief routine advertising officer.

Huawei additionally announced three recent servers in its TaiShan sweep that can be powered by using Kunpeng 920 processors. These are aimed toward company statistics centres for gigantic information tasks requiring elevated concurrency and low vigour consumption.

The Kunpeng 920 announcement follows sizzling on the heels of the AI-focused Ascend AI IP and chip series unveiled in October (see earlier in this blog).

With its emphasis on in-house design, Huawei is becoming less reliant on non-chinese language chipset suppliers akin to Intel, Qualcomm, AMD and Nvidia.

The company has been enmeshed in controversy in recent months, with a yoke of international locations banning its products in their networking infrastructure, claiming they're a safety risk.

The company has immediate connections to the chinese executive whose ‘Made in China 2025' strategy objectives ten advanced know-how areas together with AI, robotics, renewable energy and biotechnology. the U.S. has claimed this approach is a "precise existential casual to US technological leadership".

02/01/2019 Researchers consume computer discovering to diagnose dyslexia

Robot AI reading

A pair of researchers possess carried out promising consequences from a computer gaining information of scrutinize at of dyslexia amongst college children, diagnosing the circumstance efficiently in 80 per cent of circumstances with nothing human intervention

Alex Frid and Larry Manevitz from the tuition of Haifa, Israel, ran a series of assessments on 32 school infants, 17 of whom had prior to now been diaganosed with dyslexia. The babies performed a Lexical selection project (LDT) through which they were asked to judge whether strings of letters appearing on a screen possess been significant or now not.

all the way through this project, the attention movements of topics had been monitored and on the identical time electrical recreation in distinctive areas of the brain became recorded the usage of electrodes placed on the scalp.

After a preprocessing stage, the researchers used the ReleifF to extract significant aspects from the results in an attempt to classify the results. Many valuable aspects were basically create in areas of the signal traditionally regarded as noise.

by means of training their ML algorithm the usage of the 60 ‘most advantageous' features extracted from the outcomes, the researchers had been capable of diagnose dyslexia with a 79 per cent success price; using simply the ten most dependable elements, a hit fee of 70 per cent become nevertheless performed.

despite the fact, the aim was not simply to consume ML for diagnosis.

One concept of the reason of dyslexia, which influences an estimated ten per cent of the inhabitants, is that the diverse ingredients of the intellect concerned in decoding written texts office asynchronously, so alerts can arrive within the incorrect order. The enhanced the asynchrony, the greater intricate reading could be for the area.

The most arrogate change between the dyslexic and other readers changed into accompanied in exercise in the left hemisphere of the mind, specifically the left temporal node which has lengthy been concept to be essential within the technique of deciphering the written word.

The paper is posted by arxiv.org

19/12/2018 ecu knowledgeable neighborhood draws up draft AI ethics guidlines, seeks remarks

the european fee's high-stage expert neighborhood on synthetic Intelligence (AI HLEG) has launched draft ethics guidelines on trustworthy AI. The 37-page doc covers proposals to be sure AI is at each and every times human-centric and deployed with "an righteous purpose floor in". It includes discussions round limiting color and maximising inclusiveness, as well as guaranteeing that AI is strong in design and implementation so that it does not reason adventitious hurt.

AI HLEG boils down the core necessities for steadfast AI into ten wide areas: Accountability; information governance; Design for all; Governance of AI autonomy (human oversight); Non-discrimination; admire for (and enhancement of) human autonomy; respect for privacy; Robustness; protection; and Transparency.

It appears at each and every of these subject matters from technical and non-technical standpoints as a way to creating counsel on how each might be ensured.

"trustworthy AI has two add-ons: (1) it would admire fundamental rights, apposite legislation, and core concepts,making inescapable 'ethical goal'; and (2) it should be technically powerful and official," the file notes in its conclusion.

"although, even with the best of intentions, using AI can result in unintended harm. for this reason ... AI HLEG has developed a framework to truly do in obligate steadfast AI, providing concrete tips on its achievement."

The group is in the hunt for remarks on its draft proposals earlier than 18 January. In March a closing edition may be offered to the commission.

10/12/2018 Pharma giant Merck in deal to consume AI for drug discovery

the consume of AI in drug discovery - identifying promising molecules and trying out their suitability the consume of models in preference to sufferers - has been a spotlight of the pharmaceutical industry for a while. customarily drugs require years (and an colossal amount of money) to circulation from the lab into production.

within the latest movement, pharmaceutical giant Merck is to licence an AI-primarily based drug screening platform from Canadian biotechnology enterprise Cyclica as a section of a yr-lengthy trial.

Cyclica's Ligand specific is a drug screening tool which Cyclica says is a "cloud-primarily based platform that monitors small-molecule medicine in opposition t repositories of structurally-characterised proteins or ‘proteomes' to check polypharmacological profiles."

via understanding how a small-molecule drug will engage with each and every proteins in the physique, scientists can prioritise candidate molecules for drugs, realizing feasible aspect outcomes, and identify genetic adaptations which might possess an sequel on the binding of the proposed drug to the target protein. yet another consume is investigating recent makes consume of for present medication.

Small-molecule medication customarily target particular proteins associated with disorder, but once in the constitution they may additionally bind to different proteins too, and the aspect effects are arduous to call within the lab, leading to lengthy R&D and trial approaches. but AI-based mostly strategies can aid build a full photograph of the doubtless interactions of a particular molecule.

Friedrich Rippmann, Computational Chemistry & Biology director at Merck said the aim is to identify promising molecules and test them as promptly as viable.

"Assessing recent technologies is central to how they are able to enhance their discovery programmes, and ersatz intelligence purposes like Ligand express will deliver essential insights to raise how they suppose about target identification to assist phenotypic screening and off-goal profiling in commonplace," Rippman observed.

"artificial intelligence has the vigor to acquire the prior to now impossible a fact - we're wanting to harness these recent possibilities to assist power the discoveries that can radically change the lives of americans plagued by intricate-to-treat ailments," added Belén Garijo, member of the executive board and CEO Healthcare at Merck.

07/12/2018 AI cracks text-based captchas

A group of desktop scientists has developed a brand recent machine gaining information of application that can crack the textual content-primarily based captchas still used by using many web sites to protect towards bots in a fraction of a 2d.

The application changed into developed via scientists from Lancaster tuition within the UK, Northwest college within the US and Peking institution in China. It makes consume of deep learning ideas and its makers title a plenty better success price in comparison to different captcha assault strategies.

It uses Generative Adversarial community (GAN) to decode the captchas, developing synthetic captchas which are used to instruct the bottom solver algorithm. here is then excellent-tuned using a smaller set of precise captchas. this protects time and energy, with simply 500 precise captchas required to coach the assault programme.

In assessments on 33 captcha schemes, some used with the aid of the likes of Wikipedia, Google, eBay and Microsoft, the software turned into able to solve a captcha inside 0.05 seconds when elope on computer pics processing unit (GPU).

It become moreover in a position to evade advanced safety points and demostrated a immoderate stage of accuracy.

"It enables an adversary to launch an storm on capabilities, akin to Denial of carrier assaults or spending spam or phishing messages, to steal personal records and even forge person identities," pointed out Guixin Ye, a researcher on the challenge, which become introduced on the ACM conference on laptop and Communications safety (CCS) 2018 in Toronto.

"Given the immoderate success fee of their routine for many of the textual content captcha schemes, sites should still be forsaking captchas."

14/11/2018 facebook, Google and Twitter consume AI to tune unlawful drug dealing

throughout his Somewhat feeble 'grilling' with the aid of US Congress over Cambridge Analytica and other topics concerning the possess an sequel on of his social networks, one question that did elicit a (relatively) direct response from sign Zuckerberg turned into the unlawful sale of drugs on fb and Instagram - most likely as a result of he may consume his conventional inventory admit of throwing some more AI at the issue.

The opioid juncture is a uncooked difficulty in the US: seventy two,000 people died from overdoses in 2017 on my own.

Now facebook has mentioned it is actively the consume of AI to music down buyers, coordinating its efforts with specialists together with forensic labs and local and country wide organisations. Google and Twitter are moreover worried in the collaboration.

facebook's vice chairman of US public coverage Kevin Martin laid out the company's considering in a blog submit.

"We are looking to acquire a must-have supplies for medication more convenient to locate. When individuals search counsel about opioids on facebook and Instagram, they direct them to SAMSHA's [Substance abuse and Mental Health Services Administration] countrywide Helpline counsel page and different materials without impregnate and personal medication and schooling," he referred to.

"we possess now additionally begun to roll out proactive detection on fb and Instagram to assume down more content material that violates their policies earlier than people might moreover note or file it. Their expertise is capable of realize content that contains photographs of drugs and depicts the intent to promote with suggestions akin to cost, cellphone numbers or usernames for other social media money owed.

"through catching more posts immediately, this know-how allows for their team to acquire consume of their skills as a substitute to investigate money owed, Pages, organizations and hashtags, as well as work with experts to spot the next tendencies."

Susan Molinari, vice chairman for public coverage at Google, pointed out that fifty,000 searches about selected opioid medication were made day after day on the hunt engine. 

"We recognize overwhelmingly the americans who are looking for assist are the parents or family members of opioid clients, so they comprehend that if they will push them toward companies like the Partnership for Drug-Free kids, then we're getting them rapid connections," Molinari mentioned.

The efforts up to now are each and every about blockading content material and nudging users against getting assist in preference to reporting transgressors to legislation enforcement.

24/10/2018 Oracle acquires AI enterprise-intelligence enterprise DataFox

Oracle has acquired DataFox, a SaaS AI company that crunches significant volumes of facts on public and private businesses and feeds the results into an AI engine to create business-intelligence that purchasers can add to their CRM.

The San Francisco-primarily based startup received initial funding from Google Ventures in 2014 and counts Bain Capital, NetApp and Goldman Sachs amongst its purchasers. Co-founder and CEO Bastiaan Janmaat turned into a growth equity analyst at Goldman Sachs earlier than founding the company, and the funding fiscal institution has a stake in DataFox.

In a letter to DataFox shoppers and companions, Steve Miranda, executive VP applications evolution at Oracle, noted: "The composite of Oracle and DataFox will multiply Oracle Cloud applications with an in depth set of AI-derived business-stage records and signals, enabling purchasers to attain even improved selections and enterprise consequences."

DataFox pulls counsel on thousands and thousands of agencies from dissimilar sources together with information articles, digital properties and 'unique indicators' and analyses them to give true-time information on when a corporation's fortunes should be would becould very well be about to alternate. Oracle says it plans to "enrich" its cloud purposes comparable to ERP, CX, HCM and SCM with "AI-driven enterprise-degree statistics". possibly the concept is to steal a march on cloud compeition from the likes of Salesforce.

phrases of the acquisition haven't been disclosed.

19/10/2018 UK supermarkets to trial AI checkouts for age-verification

Facial attention technology is to be trialled by UK supermarkets for age verification purposes, with a number of as-yet-unidentified stores rolling out the scanning tech at self-service checkouts this year and greater extensively in 2019.

The rollout is being led through US supplier NCR, which makes self-service checkout machines for Tesco and Asda amongst others. The enterprise will integrate an 'AI-powered digital camera' (whatever that can be) into the checkout machines, which should be able to evaluate the age of valued clientele when they're buying constrained gadgets like cigarettes and alcohol. examine greater on this myth privilege here.

19/10/2018 AI - where does the liability lie?

Emma Stevens, Associate Solicitor – Dispute Resolution, Coffin Mew

The arguments involving liability in the adventure of error or incident are starting to expand. As developments proceed, and using AI turns into extra mainstream, there'll increasingly be situations which appellation in to query who has legal responsibility for the programs in use.

So says Emma Stevens, affiliate solicitor - dispute resolution, at law enterprise Coffin Mew listed here for Computing.

nearly each and every of the current legislations and case legislation with regards to liability and duty in cases of negligence drastically pre-dates the continuing robotics revolution. It is limpid that the legal device has loads of ground to cover earlier than it will possibly effortlessly alter such advances and the present legislations will should be translated to result to situations the spot considering the fact that the office and influence of AI and robotics become not up to now necessary.

organizations could be splendid to acquire themselves vigilant about the technological advances in the sectors wherein they function, to acquire sure that their contracts are limpid concerning liability (both frequently and for AI) and that they've ample coverage in region for any programs used, where applicable.

sixteen/10/2018 it's massive companies which are making the operating in machine discovering, survey

A survey of records scientists, application engineers, architects and senior management has create that gigantic organizations are taking the lead of their experiments with machine researching, with respondents in colossal establishments greater more likely to believe their efforts as 'sophisticated' and to possess their early successes rewarded by way of expanding budgets than those in smaller establishments.

About half of the respondents were create within the US, 1 / 4 in Asia with the remainder based elsewhere. The survey changed into performed by means of Algorithmia, a US traffic providing a industry for computer-discovering models.

across the total pattern, the main drivers for deploying machine learning models had been producing consumer insights and intelligence and enhancing the customer event. despite the fact, in gigantic companies enhancing consumer loyalty topped the record, outlined with the aid of fifty nine per cent. colossal firms had been additionally extra more likely to mention chopping fees as being a motivating drive.

simply 10 per cent of corporations counted themselves as subtle of their consume of AI and laptop learning. The record notes that the kindly of corporations that pioneered massive information recommendations a number of years again moreover possess a headstart when it comes to deploying machine getting to know models. they possess got the records, the infrastructure and the skills required to construct proprietary internal structures - or 'AI layers'  - on which to deploy. Examples comprehend fb's FB Learner, Netflix's workstation records Platform and Twitter's BigHead. It looks doubtless that this lead widen as investment follows success.

A statistic that demonstrates the common immaturity of the container is the proven fact that fifty five per cent of efforts are driven by IT compared with 37 per cent through the company.

12/10/2018 China will overtake the USA in AI, predicts former president of Google China Kai-Fu Lee

Kai-Fu Lee, head of VC company Sinovation Ventures and former president of Google China, says that AI's impact can be massively disruptive to everything from the geopolitical power stability to the job market and peoples′ particular person emotions of self price. whereas one of the alterations will be for the better, many will not, he says, warning in opposition t the techno-utopianism medium in Silicon Valley.

The velocity of the arrival AI revolution makes parallels with the job creation that accompanied the proliferation of electrical power and the industrial revolution redundant, Lee argued.

"those past technological revolutions took a century or longer," Lee defined, in a fascinating if discomfiting interview with IEEE Spectrum. "That gave people time to grow, and boost, and invent recent jobs. however they possess basically one generation with AI, and that's an terrible lot less time."

"we now possess opened Pandora's field," Lee went on, contrasting AI with different technological threats. "We did, as humans, control the proliferation of nuclear weapons, but that expertise become covert and required a tremendous volume of capital funding. In AI, the algorithms are neatly confidential to many americans, and it's no longer viable to forbid people to acquire consume of them. school college students are using them to birth corporations."

Lee believes the incontrovertible fact that the algorithms are without problems obtainable ability that the countries with probably the most computing vigour - and essentially the most centralised command buildings - will net acquire the operating, finally exporting their improvements to others that might are attempting to sluggish the tide to cushion its impacts. China has gigantic merits over current chief the USA, he talked about, as agencies akin to Tencent, which has shut connections to the chinese govt, possess the facts, the infrastructure and a staff that′s Somewhat organized to net stuck into the greater humdrum parts of developing AI.

"chinese entrepreneurs ascertain areas where there may be enough facts and a commercially practicable utility of AI, and then they work in reality tough to acquire the utility work. it's frequently very hard, soiled, grotesque work. The facts isn't surpassed to you on a silver platter."

a mighty deal of the gaining information of records for the ML algorithms comes from purposes like Tencent′s all-encompassing WeChat app, which is "facebook, Twitter, iMessage, Uber, Expedia, Evite, Instagram, Skype, PayPal, GrubHub, LimeBike, WebMD, Fandango, YouTube, Amazon and eBay" rolled into one. particular suggestions about a gigantic proportion of China′s great population resides in one vicinity. And measurement matters in case you're working towards neural networks.

These factors, together with the chinese language government′s capacity to squash any opposition to developments like driverless vans, are each and every within the country′s favour because it seeks to turn into the dominant obligate in AI.

Whichever vigor bloc subsequently takes the lead, the precise problem, says Lee, will be how to manage societies characterised by expanding inequality and the loss of up to 50 per cent of latest jobs, many without a glaring option office for those that dangle them, over the arrival a long time.

eleven/10/2018 recent AI-focused bulletins from Nvidia and Huawei

snap shots processing solid Nvidia has introduced an open-source GPU-acceleration platform referred to as Rapids which is aimed squarely at facts scientists who deserve to crunch great volumes of statistics. Nvidia claims that for computing device getting to know-class consume cases Rapids has proved to be 50 instances quicker than CPU-most effective programs.

Unveiled the day past in Munich, Rapids is a two-12 months-historic collaboration between Nvidia engineers and Python contributors, edifice on Apache Arrow, Pandas and Scikit-be taught. it's launched at rapids.ai below the Apache 2.0 open-supply licence.

"Rapids connects the facts science ecosystem by way of bringing collectively customary capabilities from numerous libraries and adding the vigor of GPU acceleration." the enterprise says in its weblog.

meanwhile, Huawei has unveiled two AI-concentrated chips of its personal. "As section of its full-stack AI portfolio, Huawei nowadays unveiled the Ascend AI IP and chip sequence, the realm's first AI IP and chip collection that natively serves each and every scenarios, presenting most advantageous TeraOPS per watt," announces the business's press liberate. "Their unified architecture additionally makes it effortless to installation, migrate, and interconnect AI functions across distinct situations," it says.

Alibaba, the "chinese Amazon" which is investing heavily in AI capailities is additionally reported to be developing a recent AI chip for release next 12 months.

10/10/2018 Apple buys laptop discovering enterprise Spektral

Apple had saved its $30m acquisition of digital fact (VR) solid Spektral final year a covert except Danish newspaper Brsen acquired hang of the story, studies Apple Insider.

Spektral, whose founders possess now joined Apple, was a startup specialising in desktop imaginative and prescient, using deep learning innovations and GPU hardware to improve the true-time processing of images and video at once from the camera. Apple is favourite to be eager to net ahead within the sphere of augmented reality (AR), and Apple Insider speculates that this may be at the back of the acquisition. Apple currently modified the design of iPhone cameras to stronger aid AR and VR it notes.

10/10/2018 What's recent in Spark and laptop learning?

growing advantageous laptop researching fashions is a tricky job, but making fashions which are strong satisfactory to sheperd company tactics operationally is way tougher nonetheless. here is why the internet giants construct their own structures to assist their information scientists after which engineers. Matei Zaharia and Andy Konwinski of Databricks informed Computing about two open source projects which are designed to deliver such capabilities to within the compass of mere mortals. ML circulate is a framework for standardising and packaging workflows and models, while challenge Hydrogen improves the mixing of well-known deep gaining information of frameworks akin to Tensorflow and PyTorch with Apache Spark. examine the full myth privilege here.

09/10/2018 self reliant agents are the next section of traffic AI, claims Fetch.AI

What if AI may tackle advanced negotiation projects with out requiring human intervention? this is where they are going next, in accordance with Cambridge-based startup Fetch.AI, which lately partnered with Clustermarket, a reserving platform for loaning scientific device. the consume of the gadget, instruments are represented with the aid of independent brokers which navigate a digital landscape looking for the best possible deal for themselves and optimising availability and value average. examine more privilege here.


Oracle employer (ORCL) CEO Safra Catz And sign Hurd On Q1 2019 results - salary call Transcript | killexams.com existent Questions and Pass4sure dumps

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NetSuite CEO Evan Goldberg: Oracle ownership is symbiotic | killexams.com existent questions and Pass4sure dumps

Evan Goldberg, founder and chief executive officer of NetSuite, contends that the software-as-a-service company has amplified itself since being acquired by Oracle in 2016.

Arguably, the company did possess “made at Oracle” stamped on it from the beginning. Oracle founder Larry Ellison was a major shareholder, and was a mentor to Goldberg.

He still is. Goldberg moreover confirms that Ellison is as comical in existent life as he is on stage. “He has an extraordinary sense of humour,” he says. “A lot of very brilliant people do. He is self-deprecating, and he can note the absurdity in a lot of things.”

Goldberg says Ellison’s energetic involvement in each and every the technology aspects of Oracle might possess approach as surprise to some NetSuite employees, but not to him. “Very soon after the acquisition, Larry came and spoke to their entire R&D product evolution organisation,” he says. “He knew exactly what they did, how they did it, and what their value proposition was. He started the company – I reflect he gets it.”

Goldberg originally joined Oracle straight from Harvard in 1987 when it had about 900 employees.

NetSuite, which he founded in 1998, was previously a cloud applications solid called NetLedger. He recalls: “We started a few months before salesforce.com. They had a focus on a complete traffic management suite for small and growing, and mid-market companies. They moved up the ladder as they grew out the product, but they kept their eyes on that prize during the 18 years they were an independent company, getting immediate to $1bn in annual revenue.

“Oracle is investing very heavily in NetSuite – in R&D, but moreover in expanding internationally”

Evan Goldberg, NetSuite

“But then Oracle purchased NetSuite to complete their cloud portfolio for ERP [enterprise resource planning] and traffic management SaaS applications for gigantic companies. They were not as focused on companies that were going from the garage to IPO [initial public offering], which has been their focus. But it was Larry’s vision to deliver – initially accounting – software over the web [in 1998]. They were always cousin companies, and for me it’s a coming back. I spent the first eight years of my career at Oracle.”

Here is an edited extract of an interview Goldberg did with Computer Weekly earlier this month.

How are things different for NetSuite as section of Oracle?

Goldberg: Oracle is investing very heavily in NetSuite. In R&D, but moreover in expanding internationally – the Nordics, Benelux, France – whereas previously, their international focus was very much UK. But that moreover benefits UK customers as they expand internationally, making sure NetSuite works, getting everything privilege for whichever locality, in terms of language, customs, tax, payment options, shipping, and so on.

It’s provided us with a even of focus we’ve not had in a long time. One of the first things that [Oracle CEO] sign Hurd said after the acquisition was that NetSuite would exist in the market for ever.

And under the covers, they will be delivering a brand-new analytics engine, with real-time data, and that is the sort of thing they can now do. One of the reasons that I stayed was to note through some of these deep investments in the platform to acquire NetSuite more flexible, more verticalised, so that it is suitable for each individual business.

When you reflect of your market, is it very much small to medium, but fast-growing – as opposed to just SME?

Goldberg: One of the things they possess done at Oracle is deliver SuiteSuccess editions. That’s how their customers buy NetSuite – it is more than just a software application, it is the entire process by which they interject it into their lifecycle.

They might not be fast-growing, but typically they are businesses that are geographically distributed in several countries. I’d mumble it’s companies that possess outgrown their initial fiscal application, whether that’s QuickBooks in the US or Sage in the UK, once their traffic has become more complex.

That’s why I started NetSuite in the first place, because I could see, from another startup, I didn’t possess anything that could tie everything together in the company and enable me to note everything going on in my traffic in a dashboard.

But, for example, American Express spun off its traffic travel company GBT [Global traffic Travel] and that runs on NetSuite. They finish possess companies that possess grown up with us from hundreds of millions of dollars to a billion plus. Now there may be companies where complexity goes to such a degree that Oracle cloud application is a rational destination, but is quite rare. They possess been able to scale.

In the context of a more generic shift to the cloud, what finish you note as NetSuite’s enduring value proposition?

Goldberg: Initially, they were selling the anytime, anywhere aspect of the cloud – although it wasn’t called the cloud then; it was ASP [application service provider] or web applications. And initially they ran into resistance. You had [Salesforce CEO] Marc Benioff selling software-as-a-service sales people. But finance people are by nature more conservative, and they had to mumble to them: “You are reluctant to do your finance information in the cloud, yet your sales contact information is there.” And I can’t negate Salesforce.com’s hype created a wave for us.

But you’re right. The whole narrative has flipped. Now, it’s “why would I want my information to be on my computers?”. So it has to be about more than just the cloud for us. What they possess approach back to is the other key component of their strategy, which is to deliver a single application across not just financial, not just ERP, but commerce, and HR, with SuitePeople.

The ultimate engage is each and every of your information in one place, with a single UI for each and every your users. That is what we’re hanging their hat on, and for a variety of businesses. They possess extraordinary charities using us, like Compassion in World Farming in the UK. These fast-growing charities need the same visibility into their traffic as for-profit companies.

What are the benefits of Oracle’s autonomous database and cloud drive for NetSuite, given that your customers won’t be employing lots of DBAs [database administrators] anyway?

Goldberg: They are affecting NetSuite to the Oracle Cloud Infrastructure (OCI). For instance, they will be delivering to German customers from a German datacentre over the OCI. And the Oracle Cloud Infrastructure engage is the same benefits for us as any other business. They can focus on delivering their service and let them scrutinize after the nuts and bolts of the infrastructure, and how it gets on to the internet.

How finish you note the mid-market enterprise applications market changing? SAP has made a massive turn to the customer with C/4 Hana, Microsoft Dynamics is a serious player, you possess Infor continuing to develop in the cloud, and Anaplan with fiscal planning in the cloud. What’s your read?

Goldberg: You know, it has been pretty static in their market segment. No determination is their biggest competition. They don’t note SAP, Microsoft has been very gradual to develop cloud-based versions of mid-market applications. So it’s a green sphere with a smorgasbord of local solutions internationally, and they are delivering something this uniform around the world.


AI and ML latest news: NewRelic acquires startup SignifAI to bring 'applied intelligence' to DevOps | killexams.com existent questions and Pass4sure dumps

NewRelic, the cloud-based application analytics firm, has added machine learning to its armoury in the shape of SignifAI, an Israeli-US startup focused on event intelligence - or sorting signal from uproar in the fast-moving sphere of DevOps.

SignifAI, according to its white paper, is a 'SaaS-based correlation engine that leverages AI and machine learning to rupture down the data silos create in complex enterprise IT environments.'

It integrates via APIs to around 60 commonly used monitoring and collaboration tools including Splunk, AppDynamics, Slack, AWS, Nagios - and NewRelic itself - and promises to assist developers identify the root reason of errors by sifting through events, logs, time-series data and infrastructure alerts, ranking and outputting the most probable causes to a user console or through the monitoring tool. Users can moreover train the model to improve the accuracy of the correlations.

AIOps is a relatively recent addition to the blizzard of AI and DevOps-related phrases. It refers to the consume of machine learning to analyse data collected from various IT operations tools and devices in order to spot and react to issues in existent time.

In the company's blog, NewRelic's chief product officer Jim Gochee comes down in favour of  the term ‘applied intelligence' to report the application of machine learning to the software evolution process.

"We decided to consume the term 'Applied Intelligence' to report their philosophy and approach to bringing ersatz intelligence (AI) / machine learning (ML) to their space. They chose 'Applied Intelligence' to remind ourselves to continuously reflect on the individual words and their meanings, with the goal of keeping us on track to deliver truly meaningful customer value with their AI efforts," he writes.

04/02/2019 Heathrow trials AI system for landing planes in contemptible weather

In contemptible weather, visibility from Heathrow's 87-metre tall control tower can be drastically reduced as low clouds obscure the views of the runways below.

When this happens, air traffic controllers need to depend on radar to ensure that a plane that has just landed has cleared the runway, and a margin of error must be built in for safety. This causes delays and backlogs and a 20 per cent loss of landing capacity, according to Airport World.

This is an region where AI - together with ultra HD 4K cameras - can help, believes air traffic control service NATS. The organisation has begun a trial using 20 such cameras installed in the tower together with a machine learning system called Aimee which has been developed by Canadian vendor Searidge Technologies. A similar trial is underway at Singapore's Changi Airport.

Once trained, Aimee should be able to track the aircraft from the time they land until they are limpid of the runway, even when the cameras' images are difficult to interpret by the human eye. It will then alert the air traffic controller who will acquire the final determination on whether to limpid the next arriving flight for landing. As such, Aimee is very much an aid to human determination making rather than being an autonomous control system. 

The behaviour of 50,000 arriving aircraft will be studied over the next 12 months to note how the system responds to real-world situations.

AI is likely to play an increasingly essential role in the management of air traffic in the future, including for Heathrow's planned third runway, said Heathrow's operations director, Kathryn Leahy.

"We'll be keeping a immediate eye on this trial, as the technology could possess a major role as they prepare for the expanded airport. They will watch how AI and digital towers could be used to monitor each and every three of the expanded airport's runways in future," she said.

The results of the trial will be presented to be presented to the UK Civil Aviation Authority next March.

28/01/2019 Amazon open-sources its SageMaker Neo machine learning optimisation software

Raspberry Pi Zero

Amazon has open-sourced SageMaker Neo, its software for training machine learning models and optimising the way they elope on different types of devices.

SageMaker Neo is designed to ensure that ML models elope as efficiently as possible on a variety of machines and environments. Unlike the training stage, in which models are generally honed on high-powered machines, for the inference stage, where the model makes predictions based on recent data, it may be running on much lowlier devices.

The environment can possess a gigantic sequel on the amount of time it takes for a model to infer a result and on the number of such calculations that can be elope in parallel. On edge devices in the IoT - a single board computer like a Raspberry Pi for illustration - latency and limited concurrency can be severe impediments. ML models are far from device-agnostic.

Most devices can be optimised to speed up the inference process, but this generally involves a unprejudiced bit of manual tinkering and trial and error. The original SageMaker was a model training framework, but SageMaker Neo, introduced terminal November, combines that with an optimisation stage, taking the fully trained model and generating an executable that's specific to the target device - be that a GPU or a Pi.

"Amazon SageMaker Neo automatically optimises machine learning models to perform at up to twice the speed with no loss in accuracy. You start with a machine learning model built using MXNet, TensorFlow, PyTorch, or XGBoost and trained using Amazon SageMaker. Then you select your target hardware platform from Intel, Nvidia, or Arm. With a single click, SageMaker Neo will then compile the trained model into an executable," the company says on its website, adding that the compiler uses neural networking techniques to analyse the target platform so that optimisations can be applied.

The Neo-AI project is available on Github under the Apache Software License, allowing developers to tailor the code to suit their own needs.

Other cloud firms, including Microsoft and Google, are moreover working on applying AI to the ‘intelligent edge'.

07/01/2019 Huawei announces 'highest performance ARM-based CPU' aimed at AI workloads

Huawei has announced what it claims is the world's best performing ARM-based processor.

Unveiled on Sunday, the Kunpeng 920 is purpose-built for AI workloads that involve processing great volumes of data utilising distributed storage.

In SPECint benchmarking tests, the Kunpeng 920 scored more than 930, or almost 25 per cent higher than the industry benchmark, while using 30 per cent less power than competitors, Huawei claims.

The Huawei-designed processor is manufactured on a 7-nanometer process based on the ARM architecture. It has 64 cores with clock speed 2.6GHz and 8-channel DDR4 memory.

The enhanced performance is primarily due to optimised branch prediction algorithms and an increased number of OP units, along with an improved reminiscence subsystem architecture, according to the firm.

"Today, with Kunpeng 920, they are entering an era of diversified computing embodied by multiple cores and heterogeneity. Huawei has invested patiently and intensively in computing innovation to continuously acquire breakthroughs. They will work with their customers and partners to build a fully connected, brilliant world," said William Xu, Huawei's chief strategy marketing officer.

Huawei moreover announced three recent servers in its TaiShan sweep that will be powered by Kunpeng 920 processors. These are aimed at corporate data centres for gigantic data tasks requiring elevated concurrency and low power consumption.

The Kunpeng 920 announcement follows tart on the heels of the AI-focused Ascend AI IP and chip series unveiled in October (see earlier in this blog).

With its emphasis on in-house design, Huawei is becoming less reliant on non-Chinese chipset suppliers such as Intel, Qualcomm, AMD and Nvidia.

The company has been enmeshed in controversy in recent months, with a number of countries banning its products in their networking infrastructure, claiming they are a security risk.

The company has immediate connections to the Chinese government whose ‘Made in China 2025' strategy targets ten advanced technology areas including AI, robotics, renewable energy and biotechnology. The US has claimed this strategy is a "real existential threat to US technological leadership".

02/01/2019 Researchers consume machine learning to diagnose dyslexia

Robot AI reading

A pair of researchers possess achieved promising results from a machine learning study of dyslexia among school children, diagnosing the condition successfully in 80 per cent of cases without any human intervention

Alex Frid and Larry Manevitz from the University of Haifa, Israel, ran a series of tests on 32 school children, 17 of whom had previously been diaganosed with dyslexia. The children performed a Lexical determination Task (LDT) in which they were asked to judge whether strings of letters appearing on a screen were meaningful or not.

During this task, the eye movements of subjects were monitored and at the same time electrical activity in different areas of the brain was recorded using electrodes placed on the scalp.

After a preprocessing stage, the researchers used the ReleifF to extract meaningful features from the results in an attempt to classify the results. Many valuable features were in fact discovered in areas of the signal traditionally considered as noise.

By training their ML algorithm using the 60 ‘best' features extracted from the results, the researchers were able to diagnose dyslexia with a 79 per cent success rate; using just the ten best features, a success rate of 70 per cent was still achieved.

However, the goal was not just to consume ML for diagnosis.

One theory of the reason of dyslexia, which affects an estimated ten per cent of the population, is that the different parts of the brain involved in decoding written texts operate asynchronously, so signals can arrive in the wrong order. The greater the asynchrony, the more difficult reading will be for the subject.

The greatest incompatibility between the dyslexic and other readers was observed in activity in the left hemisphere of the brain, particularly the left temporal node which has long been thought to be essential in the process of interpreting the written word.

The paper is published by arxiv.org

19/12/2018 EU expert group draws up draft AI ethics guidlines, seeks feedback

The European Commission's High-Level Expert Group on ersatz Intelligence (AI HLEG) has released draft ethics guidelines on trustworthy AI. The 37-page document covers proposals to ensure AI is always human-centric and deployed with "an ethical purpose ground in". It includes discussions around limiting color and maximising inclusiveness, as well as ensuring that AI is robust in design and implementation so that it does not reason unintentional harm.

AI HLEG boils down the core requirements for trustworthy AI into ten broad areas: Accountability; Data governance; Design for all; Governance of AI autonomy (human oversight); Non-discrimination; Respect for (and enhancement of) human autonomy; Respect for privacy; Robustness; Safety; and Transparency.

It looks at each of these topics from technical and non-technical standpoints with a view to creating guidance on how each might be ensured.

"Trustworthy AI has two components: (1) it should respect fundamental rights, applicable regulation, and core principles,ensuring 'ethical purpose'; and (2) it should be technically robust and reliable," the report notes in its conclusion.

"However, even with the best of intentions, the consume of AI can result in unintentional harm. Therefore ... AI HLEG has developed a framework to actually implement Trustworthy AI, offering concrete guidance on its achievement."

The group is seeking feedback on its draft proposals before 18 January. In March a final version will be presented to the Commission.

10/12/2018 Pharma giant Merck in deal to consume AI for drug discovery

The consume of AI in drug discovery - identifying promising molecules and testing their suitability using models rather than patients - has been a focus of the pharmaceutical industry for some time. Typically drugs require years (and a huge amount of money) to gallop from the lab into production.

In the latest move, pharmaceutical giant Merck is to licence an AI-based drug screening platform from Canadian biotechnology solid Cyclica as section of a year-long trial.

Cyclica's Ligand Express is a drug screening tool which Cyclica says is a "cloud-based platform that screens small-molecule drugs against repositories of structurally-characterized proteins or ‘proteomes' to determine polypharmacological profiles."

By understanding how a small-molecule drug will interact with each and every proteins in the body, scientists can prioritise candidate molecules for drugs, understanding possible side effects, and identify genetic variations which might affect the binding of the proposed drug to the target protein. Another consume is investigating recent uses for existing drugs.

Small-molecule drugs typically target specific proteins associated with disease, but once in the cadaver they may bind to other proteins too, and the side effects are arduous to call in the lab, leading to lengthy R&D and trial procedures. But AI-based techniques can assist build a full picture of the likely interactions of a particular molecule.

Friedrich Rippmann, Computational Chemistry & Biology director at Merck said the goal is to identify promising molecules and test them as quickly as possible.

"Assessing recent technologies is central to how they will further their discovery programmes, and ersatz intelligence applications like Ligand Express will provide essential insights to enhance how they reflect about target identification to support phenotypic screening and off-target profiling in general," Rippman said.

"Artificial intelligence has the power to acquire the previously unimaginable a reality - they are eager to harness these recent possibilities to assist drive the discoveries that can transform the lives of people affected by difficult-to-treat diseases," added Belén Garijo, member of the executive board and CEO Healthcare at Merck.

07/12/2018 AI cracks text-based captchas

A team of computer scientists has developed a recent machine learning program that can crack the text-based captchas still used by many websites to protect against bots in a fraction of a second.

The program was developed by scientists from Lancaster University in the UK, Northwest University in the US and Peking University in China. It uses deep learning techniques and its makers title a much higher success rate compared to other captcha storm methods.

It uses Generative Adversarial Network (GAN) to decode the captchas, creating synthetic captchas that are used to train the basis solver algorithm. This is then fine-tuned using a smaller set of existent captchas. This saves time and effort, with just 500 genuine captchas required to train the storm programme.

In tests on 33 captcha schemes, some used by the likes of Wikipedia, Google, eBay and Microsoft, the program was able to solve a captcha within 0.05 seconds when elope on desktop graphics processing unit (GPU).

It was moreover able to evade advanced security features and demostrated a elevated even of accuracy.

"It allows an adversary to launch an storm on services, such as Denial of Service attacks or spending spam or phishing messages, to steal personal data or even forge user identities," said Guixin Ye, a researcher on the project, which was presented at the ACM Conference on Computer and Communications Security (CCS) 2018 in Toronto.

"Given the elevated success rate of their approach for most of the text captcha schemes, websites should be abandoning captchas."

14/11/2018 Facebook, Google and Twitter consume AI to track illegal drug dealing

During his rather feeble 'grilling' by US Congress over Cambridge Analytica and other topics related to the influence of his social networks, one question that did elicit a (relatively) direct response from sign Zuckerberg was the illegal sale of drugs on Facebook and Instagram - presumably because he could consume his favourite stock admit of throwing some more AI at the problem.

The opioid juncture is a raw issue in the US: 72,000 people died from overdoses in 2017 alone.

Now Facebook has said it is actively using AI to track down dealers, coordinating its efforts with experts including forensic labs and local and national organisations. Google and Twitter are moreover involved in the collaboration.

Facebook's vice president of US public policy Kevin Martin laid out the company's thinking in a blog post.

"We want to acquire vital resources for treatment easier to find. When people search for information about opioids on Facebook and Instagram, they direct them to SAMSHA's [Substance abuse and Mental Health Services Administration] National Helpline Information Page and other resources for free and confidential treatment and education," he said.

"We've moreover begun to roll out proactive detection on Facebook and Instagram to assume down more content that violates their policies before people may note or report it. Their technology is able to detect content that includes images of drugs and depicts the intent to sell with information such as price, phone numbers or usernames for other social media accounts.

"By catching more posts automatically, this technology allows their team to consume their expertise instead to investigate accounts, Pages, Groups and hashtags, as well as work with experts to spot the next trends."

Susan Molinari, vice president for public policy at Google, said that 50,000 searches about specific opioid drugs were made each day on the search engine. 

"We know overwhelmingly the people who are searching for assist are the parents or family members of opioid users, so they know that if they can push them toward organisations like the Partnership for Drug-Free Kids, then we're getting them instant connections," Molinari said.

The efforts so far are each and every about blocking content and nudging users towards getting assist rather than reporting transgressors to law enforcement.

24/10/2018 Oracle acquires AI company-intelligence solid DataFox

Oracle has acquired DataFox, a SaaS AI solid that crunches great volumes of data on public and private businesses and feeds the results into an AI engine to create company-intelligence that customers can add to their CRM.

The San Francisco-based startup received initial funding from Google Ventures in 2014 and counts Bain Capital, NetApp and Goldman Sachs among its customers. Co-founder and CEO Bastiaan Janmaat was a growth equity analyst at Goldman Sachs before founding the firm, and the investment bank has a stake in DataFox.

In a letter to DataFox customers and partners, Steve Miranda, executive VP applications evolution at Oracle, said: "The combination of Oracle and DataFox will enhance Oracle Cloud Applications with an extensive set of AI-derived company-level data and signals, enabling customers to compass even better decisions and traffic outcomes."

DataFox pulls information on millions of businesses from multiple sources including word articles, digital properties and 'unique signals' and analyses them to provide real-time information on when a company's fortunes might be about to change. Oracle says it plans to "enrich" its cloud applications such as ERP, CX, HCM and SCM with "AI-driven company-level data". Presumably the feeling is to steal a march on cloud compeition from the likes of Salesforce.

Terms of the acquisition possess not been disclosed.

19/10/2018 UK supermarkets to trial AI checkouts for age-verification

Facial recognition technology is to be trialled by UK supermarkets for age verification purposes, with a few as-yet-unidentified stores rolling out the scanning tech at self-service checkouts this year and more widely in 2019.

The rollout is being led by US vendor NCR, which makes self-service checkout machines for Tesco and Asda among others. The company will integrate an 'AI-powered camera' (whatever that may be) into the checkout machines, which will be able to evaluate the age of shoppers when they are buying restricted items like cigarettes and alcohol. Read more on this myth here.

19/10/2018 AI - where does the liability lie?

Emma Stevens, Associate Solicitor – Dispute Resolution, Coffin Mew

The arguments regarding liability in the event of error or incident are birth to expand. As developments continue, and the consume of AI becomes more mainstream, there will increasingly be cases which call in to question who has liability for the systems in use.

So says Emma Stevens, associate solicitor - dispute resolution, at law solid Coffin Mew in this article for Computing.

The majority of the existing legislation and case law in relation to liability and duty in cases of negligence significantly pre-dates the ongoing robotics revolution. It is limpid that the legal system has a lot of ground to cover before it can effectively regulate such advances and the existing law will need to be translated to apply to situations where considering the role and impact of AI and robotics was not previously necessary.

Businesses would be sensible to acquire themselves vigilant of the technological advances in the sectors in which they operate, to ensure that their contracts are limpid regarding liability (both generally and for AI) and that they possess adequate insurance in spot for any systems used, where appropriate.

16/10/2018 It's gigantic companies that are making the running in machine learning, survey

A survey of data scientists, software engineers, architects and senior management has create that great organisations are taking the lead in their experiments with machine learning, with respondents in great organisations more likely to deem their efforts as 'sophisticated' and to possess their early successes rewarded by increasing budgets than those in smaller firms.

About half of the respondents were located in the US, a quarter in Asia with the remainder based elsewhere. The survey was conducted by Algorithmia, a US company offering a marketplace for machine-learning models.

Across the entire sample, the main drivers for deploying machine learning models were generating customer insights and intelligence and improving the customer experience. However, in great enterprises improving customer loyalty topped the list, mentioned by 59 per cent. great enterprises were moreover more likely to mention cutting costs as being a motivating force.

Just 10 per cent of companies counted themselves as sophisticated in their consume of AI and machine learning. The report notes that the sort of companies that pioneered gigantic data techniques a few years back moreover possess a headstart when it comes to deploying machine learning models. They possess the data, the infrastructure and the skills required to build proprietary internal platforms - or 'AI layers'  - on which to deploy. Examples comprehend Facebook's FB Learner, Netflix's Notebook Data Platform and Twitter's BigHead. It seems likely that this lead widen as investment follows success.

A statistic that demonstrates the generic immaturity of the sphere is the fact that 55 per cent of efforts are driven by IT compared with 37 per cent by the business.

12/10/2018 China will overtake the US in AI, predicts former president of Google China Kai-Fu Lee

Kai-Fu Lee, head of VC solid Sinovation Ventures and former president of Google China, says that AI's influence will be hugely disruptive to everything from the geopolitical power equipoise to the job market and peoples′ individual feelings of self worth. While some of the changes will be for the better, many will not, he says, warning against the techno-utopianism common in Silicon Valley.

The speed of the coming AI revolution makes parallels with the job creation that accompanied the proliferation of electrical power and the industrial revolution redundant, Lee argued.

"Those earlier technological revolutions took a century or longer," Lee explained, in a fascinating if discomfiting interview with IEEE Spectrum. "That gave people time to grow, and develop, and invent recent jobs. But they possess basically one generation with AI, and that's a lot less time."

"We've opened Pandora's box," Lee went on, contrasting AI with other technological threats. "We did, as humans, control the proliferation of nuclear weapons, but that technology was covert and required a huge amount of capital investment. In AI, the algorithms are well known to many people, and it's not possible to forbid people to consume them. College students are using them to start companies."

Lee believes the fact that the algorithms are easily available means that the nations with the most computing power - and the most centralised command structures - will net acquire the running, ultimately exporting their innovations to others that might try to gradual the tide to cushion its impacts. China has gigantic advantages over current leader the USA, he said, as companies such as Tencent, which has immediate connections to the Chinese government, possess the data, the infrastructure and a workforce that′s quite prepared to net stuck into the more humdrum parts of developing AI.

"Chinese entrepreneurs find areas where there's enough data and a commercially viable application of AI, and then they work really arduous to acquire the application work. It's often very hard, dirty, unpleasant work. The data isn't handed to you on a silver platter."

Much of the learning data for the ML algorithms comes from applications like Tencent′s all-encompassing WeChat app, which is "Facebook, Twitter, iMessage, Uber, Expedia, Evite, Instagram, Skype, PayPal, GrubHub, LimeBike, WebMD, Fandango, YouTube, Amazon and eBay" rolled into one. particular information about a great proportion of China′s huge population resides in one place. And size matters when you're training neural networks.

These factors, together with the Chinese government′s ability to squash any opposition to developments like driverless trucks, are each and every in the country′s favour as it seeks to become the dominant obligate in AI.

Whichever power bloc ultimately takes the lead, the existent challenge, says Lee, will be how to manage societies characterised by increasing inequality and the loss of up to 50 per cent of current jobs, many with no obvious alternative role for those that hold them, over the coming decades.

11/10/2018 recent AI-focused announcements from Nvidia and Huawei

Graphics processing solid Nvidia has announced an open-source GPU-acceleration platform called Rapids which is aimed squarely at data scientists who need to crunch great volumes of data. Nvidia claims that for machine learning-type consume cases Rapids has proved to be 50 times faster than CPU-only systems.

Unveiled yesterday in Munich, Rapids is a two-year-old collaboration between Nvidia engineers and Python contributors, edifice on Apache Arrow, Pandas and Scikit-learn. It is released at rapids.ai under the Apache 2.0 open-source licence.

"Rapids connects the data science ecosystem by bringing together accepted capabilities from multiple libraries and adding the power of GPU acceleration." the solid says in its blog.

Meanwhile, Huawei has unveiled two AI-focused chips of its own. "As section of its full-stack AI portfolio, Huawei today unveiled the Ascend AI IP and chip series, the world's first AI IP and chip series that natively serves each and every scenarios, providing optimal TeraOPS per watt," proclaims the company's press release. "Their unified architecture moreover makes it effortless to deploy, migrate, and interconnect AI applications across different scenarios," it says.

Alibaba, the "Chinese Amazon" which is investing heavily in AI capailities is moreover reported to be developing a recent AI chip for release next year.

10/10/2018 Apple buys machine learning solid Spektral

Apple had kept its $30m acquisition of virtual reality (VR) solid Spektral terminal year a covert until Danish newspaper Brsen got hold of the story, reports Apple Insider.

Spektral, whose founders possess now joined Apple, was a startup specialising in computer vision, using deep learning techniques and GPU hardware to improve the real-time processing of images and video directly from the camera. Apple is known to be keen to net ahead in the sphere of augmented reality (AR), and Apple Insider speculates that this may be behind the acquisition. Apple recently changed the design of iPhone cameras to better support AR and VR it notes.

10/10/2018 What's recent in Spark and machine learning?

Creating useful machine learning models is a tough job, but making models that are robust enough to support traffic processes operationally is far tougher still. This is why the web giants build their own platforms to support their data scientists and then engineers. Matei Zaharia and Andy Konwinski of Databricks told Computing about two open source projects that are designed to bring such capabilities to within the compass of mere mortals. ML flux is a framework for standardising and packaging workflows and models, while Project Hydrogen improves the integration of accepted deep learning frameworks such as Tensorflow and PyTorch with Apache Spark. Read the full myth here.

09/10/2018 Autonomous agents are the next angle of enterprise AI, claims Fetch.AI

What if AI could assume on complex negotiation tasks without requiring human intervention? This is where they are going next, according to Cambridge-based startup Fetch.AI, which recently partnered with Clustermarket, a booking platform for loaning scientific equipment. Using the system, instruments are represented by autonomous agents which navigate a virtual landscape seeking the best possible deal for themselves and optimising availability and price overall. Read more here.


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