Artificial intelligence is rapidly changing many aspects of how we work and live. (How many stories did you read last week about self-driving cars and job-stealing robots? Perhaps your holiday shopping involved some AI algorithms, as well.) But despite the constant flow of news, many misconceptions about AI remain.
AI doesn’t think in our sense of the word at all, Scriffignano explains. “In many ways, it’s not really intelligence. It’s regressive.”
IT leaders should make deliberate choices about what AI can and can’t do on its own. “You have to pay attention to giving AI autonomy intentionally and not by accident,”
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Tomi Engdahl says:
https://www.uusiteknologia.fi/2018/09/03/ensimmaiset-verkon-tekoalykurssilta-suomenkielinen-versio-tulossa/
Tomi Engdahl says:
The 8K TV You Can Actually Buy! [Samsung Q900R QLED 8K] | The Tech Chap
https://www.youtube.com/watch?v=yajKZVdUWBQ
The Samsung Q900R QLED 8K TV is the WORLD’s first 8K TV you can actually buy! This 8K HDR QLED TV comes in 4 sizes (65-85″), has a new 8K Quantum Processor, Up to 4000 Nit Brightness, 8K HDR, and AI Upscaling! But why would ANYONE buy this?
Tomi Engdahl says:
With $65M, ThinCI Joins Elite AI Startup Club
Series C funding includes Daimler investment
https://www.eetimes.com/document.asp?doc_id=1333664
With a host of chip startups — each claiming development of a unique processing architecture ideally suited for AI/machine learning— all hot and bothered in an overheated AI market, how can you tell who’s ahead of whom?
With a recently closed Series C round of $65 million, ThinCI Inc., an AI processor company (El Dorado Hills, California), joins an exclusive club of well-heeled AI hardware startups. Other members include Wave Computing, which has raised $117.3 million, Cerebras at $112 million, and Graphcore at $110 million.
Tomi Engdahl says:
Processing In Memory
https://semiengineering.com/processing-in-memory/
Growing volume of data and limited improvements in performance create new opportunities for approaches that never got off the ground.
Tomi Engdahl says:
Deep Learning for Computer Vision with TensorFlow
https://tensorflow.embedded-vision.com/?utm_source=Mailing+List&utm_campaign=2ebc55db1a-20180905_TFTraining_SJO_NonMem_T4&utm_medium=email&utm_term=0_3ef87432f1-2ebc55db1a-354463329&mc_cid=2ebc55db1a&mc_eid=3e001376d2
Tomi Engdahl says:
China is beating the US on AI, says noted investor Kai-Fu Lee
https://techcrunch.com/2018/09/05/china-is-beating-the-us-on-ai-says-noted-investor-kaifu-lee/?sr_share=facebook&utm_source=tcfbpage
America may have created AI, but China is taking the ball and running when it comes to one of the world’s most pivotal technology innovations.
That’s according to Kai-Fu Lee, a world-renowned AI expert who founded Sinovation, a China-U.S. fund that raised its fourth fund worth $1 billion earlier this year.
Speaking at TechCrunch Disrupt San Francisco, Lee — who led Google in China before it left the country — said any lead America’s tech industry may have enjoyed is rapidly being eroded by hungry Chinese entrepreneurs who have oodles more data at their disposal to build, train and deploy AI systems.
Tomi Engdahl says:
Frederic Lardinois / TechCrunch:
BMW debuts the AI-powered BMW Intelligent Personal Assistant for its cars, available from March 2019 in 10 countries, including US and UK, and May 2019 in China
BMW launches a personal voice assistant for its cars
https://techcrunch.com/2018/09/06/bmw-launches-a-personal-voice-assistant-for-its-cars/
Tomi Engdahl says:
TensorFlow in your Browser
https://hackaday.com/2018/04/16/tensorflow-in-your-browser/
Tomi Engdahl says:
https://js.tensorflow.org/
Tomi Engdahl says:
Artificial Intelligence — The Revolution Hasn’t Happened Yet
https://medium.com/@mijordan3/artificial-intelligence-the-revolution-hasnt-happened-yet-5e1d5812e1e7
Artificial Intelligence (AI) is the mantra of the current era. The phrase is intoned by technologists, academicians, journalists and venture capitalists alike. As with many phrases that cross over from technical academic fields into general circulation, there is significant misunderstanding accompanying the use of the phrase. But this is not the classical case of the public not understanding the scientists — here the scientists are often as befuddled as the public. The idea that our era is somehow seeing the emergence of an intelligence in silicon that rivals our own entertains all of us — enthralling us and frightening us in equal measure. And, unfortunately, it distracts us.
Tomi Engdahl says:
Robots can develop prejudices just like humans
https://techcrunch.com/2018/09/06/robots-can-develop-prejudices-just-like-humans/?sr_share=facebook&utm_source=tcfbpage
In a fascinating study by researchers at Cardiff University and MIT, we learn that robots can develop prejudices when working together. The robots, which ran inside a teamwork simulator, expressed prejudice against other robots not on their team. In short, write the researchers, “groups of autonomous machines could demonstrate prejudice by simply identifying, copying and learning this behavior from one another.”
Tomi Engdahl says:
Measuring AI startups by the right yardstick
https://techcrunch.com/2018/09/06/measuring-ai-startups-by-the-right-yardstick/?sr_share=facebook&utm_source=tcfbpage
Building a B2B AI startup is hard enough between struggling to obtain training data and fighting with major tech companies to secure talent. Building a B2B AI startup held to the well-established software-as-a-service (SaaS) metrics is even harder. While many AI businesses deliver value via software monetized by a recurring subscription like their SaaS counterparts, the similarities between the two types of businesses end there.
AI startups are a different animal
SaaS products built without data and AI offer generalized solutions to their customers. AI businesses more closely resemble a services business or consultancies because they provide solutions that become tailored to that customer’s specific needs. Like services providers or consultants, an AI product improves as it knows a customer better (as in, as it collects more data from customers with continued usage), and as it serves a broader customer base, from which it can collect best practices and make better predictions over a bigger data set.
AI businesses are not scalable right out of the gate: AI models take time and require data to train. Moreover, not all AI businesses will scale. Here are the metrics we use to tell the difference early on.
AI metrics
Intervention ratio
ROI curve
Rev-up costs
SaaS metrics aren’t enough
Tomi Engdahl says:
Dave Gershgorn / Quartz:
Healthcare AI has the same racial and gender biases as the data used to train it, which must be addressed if AI systems are to help make real medical decisions
HEAL THYSELF, ALGORITHM
If AI is going to be the world’s doctor, it needs better textbooks
https://qz.com/1367177/if-ai-is-going-to-be-the-worlds-doctor-it-needs-better-textbooks/
Imagine there was a simple test to see whether you were developing Alzheimer’s disease. You would look at a picture and describe it, software would assess the way you spoke, and based on your answer, tell you whether or not you had early-stage Alzheimer’s. It would be quick, easy, and over 90% accurate—except for you, it doesn’t work.
That might be because you’re from Africa. Or because you’re from India, or China, or Michigan. Imagine most of the world is getting healthier because of some new technology, but you’re getting left behind.
Actually, you don’t have to imagine. This scenario is real.
“When you actually talk to real doctors and patients, suddenly the things that weren’t apparent to computer scientists working in a basement with data become more evident,”
A person’s body-hair type can skew an AI’s assessment of whether or not he or she has skin cancer.
81% of participants in genome-mapping studies were of European descent.
Tomi Engdahl says:
Steve LeVine / Axios:
McKinsey study says AI adoption will add $13T/year to global production, and the companies that embrace AI now will see their cash flow double by 2030
The devilishly quiet age of AI
https://www.axios.com/quiet-artificial-intelligence-revolution-3ade583f-ca2d-4b10-bdf9-d9c75fb8418f.html
The world is in a deceptively quiet period in which some companies and countries are aggressively developing and applying early, rudimentary models of artificial intelligence, but the impact is not visible.
Why it matters: The AI revolution will arrive almost imperceptibly, but still faster than prior big technological shifts because of intense global competition and the breadth of its reach, according to a new study by the McKinsey Global Institute.
But by the second half of the next decade, a few players will be conspicuously ahead of rivals, and by 2035, there will be clear winners and losers among countries, companies and individuals.
The dividing line will be defined by those who took the coming age seriously and prepared for it and those who were passive.
China and the U.S. are at the top by themselves.
“By 2035, a lot of the game will have played,” Seong told Axios.
But, but, but, the study said, “The economic impact of AI is not guaranteed by being in a particular group of countries that look promising in terms of readiness — passivity will mean that even if the factors appear to be in place for the rapid adoption of AI, the economic benefits are unlikely to materialize.”
The big picture: AI adoption will add $13 trillion a year to global production, the report said, and an average of 1.2% to global GDP growth per year.
Among companies, those that embrace AI will see double their cash flow by 2030. Those that don’t could lose 20% of their revenue by then.
Tomi Engdahl says:
Gregory Barber / Wired:
Researchers think we may be on the verge of breakthroughs in AI’s comprehension of language similar to the AI image recognition breakthroughs of 2012 — IN 2012, ARTIFICIAL intelligence researchers revealed a big improvement in computers’ ability to recognize images by feeding …
https://www.wired.com/story/ai-can-recognize-images-but-understand-headline
Tomi Engdahl says:
LOCKHEED MARTIN AND DRONE RACING LEAGUE LAUNCH GROUNDBREAKING AI INNOVATION CHALLENGE
https://news.lockheedmartin.com/2018-09-05-Lockheed-Martin-and-Drone-Racing-League-Launch-Groundbreaking-AI-Innovation-Challenge
Lockheed Martin (NYSE: LMT) and Drone Racing League (DRL) today announced an innovation competition, challenging teams to develop artificial intelligence (AI) technology that will enable an autonomous drone to race a pilot-operated drone – and win. Participating teams will compete in a series of challenges for their share of over $2 million in prizes.
“At Lockheed Martin, we are working to pioneer state-of-the-art, AI-enabled technologies that can help solve some of the world’s most complex challenges – from fighting wildfires and saving lives during natural disasters to exploring the farthest reaches of deep space,” said Jackson. “Now, we are inviting the next generation of AI innovators to join us with our AlphaPilot Innovation Challenge. Competitors will have an opportunity to define the future of autonomy and AI and help our world leverage these promising technologies to build a brighter future.”
Tomi Engdahl says:
Tom Krazit / GeekWire:
Carnegie Mellon’s Andrew Moore to join Google Cloud as new head of AI later this year, as current leader Fei Fei Li returns to Stanford — After an interesting year for Google Cloud’s artificial intelligence group, Andrew Moore, dean of computer science at Pittsburgh’s Carnegie Mellon University …
Carnegie Mellon’s Andrew Moore to join Google Cloud as new head of AI later this year
https://www.geekwire.com/2018/carnegie-mellons-andrew-moore-join-google-cloud-new-head-ai-later-year/
Tomi Engdahl says:
Tekoäly uskoi koomapotilaiden heräävän, vaikka lääkärit eivät antaneet toivoa – tekoäly oli oikeassa
https://www.mtv.fi/lifestyle/digi/artikkeli/tekoaly-uskoi-koomapotilaiden-heraavan-vaikka-laakarit-eivat-antaneet-toivoa-tekoaly-oli-oikeassa/7065850
Doctors said the coma patients would never wake. AI said they would – and they did
https://www.scmp.com/news/china/science/article/2163298/doctors-said-coma-patients-would-never-wake-ai-said-they-would
Artificial intelligence system developed in Beijing ‘will never replace doctors’ but it can trace brain activity invisible to the human eye
Tomi Engdahl says:
SNN News: BrainChip Unveils Akida Architecture
https://www.electronicdesign.com/embedded-revolution/snn-news-brainchip-unveils-akida-architecture?NL=ED-005&Issue=ED-005_20180912_ED-005_566&sfvc4enews=42&cl=article_1_b&utm_rid=CPG05000002750211&utm_campaign=19868&utm_medium=email&elq2=ebadbebd71f2466c830a02c0f0274004
Armed with approximately 1.2 million neurons and 10 billion synapses, the Akida NSoC spiking-neural-network chip takes on training and inference tasks.
Tomi Engdahl says:
AI’s Long-Term Impact
https://semiengineering.com/ais-long-term-impact/
The McKinsey Global Institute considers what AI means for companies, countries, workers.
The key takeaway points of the report:
• “AI has large potential to contribute to global economic activity.”
• “The economic impact may emerge gradually and be visible only over time.”
• “A key challenge is that adoption of AI could widen gaps between countries, companies, and workers.”
• “How companies and countries choose to embrace AI will likely impact outcomes.”
Tomi Engdahl says:
Facebook’s ‘Rosetta’ system helps the company understand memes
https://techcrunch.com/2018/09/11/facebooks-rosetta-system-helps-the-company-understand-memes/?utm_source=tcfbpage&sr_share=facebook
Tomi Engdahl says:
Intel Execs Address the AI Talent Shortage, AI Education, and the “Cool” Factor
https://spectrum.ieee.org/view-from-the-valley/robotics/artificial-intelligence/intel-execs-address-the-ai-talent-shortage-ai-education-and-the-cool-factor
Tomi Engdahl says:
Tom GruberatTED2017
How AI can enhance our memory, work and social lives
https://www.ted.com/talks/tom_gruber_how_ai_can_enhance_our_memory_work_and_social_lives/up-next?utm_source=facebook.com&utm_medium=social&utm_campaign=tedspread-sharetrade-a
Tomi Engdahl says:
https://www.htbridge.com/blog/spencer-young-application-security-ai-cybercrime.html
Tomi Engdahl says:
Facebook’s new ‘SapFix’ AI automatically debugs your code
https://techcrunch.com/2018/09/13/facebook-sapfix-debugger/
Facebook has quietly built and deployed an artificial intelligence programming tool called SapFix that scans code, automatically identifies bugs, tests different patches and suggests the best ones that engineers can choose to implement. Revealed today at Facebook’s @Scale engineering conference, SapFix is already running on Facebook’s massive code base and the company plans to eventually share it with the developer community.
“To our knowledge, this marks the first time that a machine-generated fix — with automated end-to-end testing and repair — has been deployed into a codebase of Facebook’s scale,”
Tomi Engdahl says:
Khari Johnson / VentureBeat:
Microsoft says it acquired Lobe, a San Francisco-based startup that lets users build machine learning models using a visual interface with no coding required — Microsoft today announced it has acquired Lobe, creator of a platform for building custom deep learning models using a visual interface …
Microsoft acquires AI startup Lobe to help people make deep learning models without code
https://venturebeat.com/2018/09/13/microsoft-acquires-ai-startup-lobe-to-help-people-make-deep-learning-models-without-code/
Tomi Engdahl says:
Winning with AI
https://www.ibm.com/blogs/think/2018/09/winning-with-ai/
Since the year 2000, 52% of the companies that make up the Fortune 500 have disappeared. They have been acquired, succumbed to performance atrophy, or declared bankruptcy. In this hyper-competitive marketplace, winners and losers are being declared every day. And while artificial intelligence (AI) can be the valve to these pressures, for many, drafting a playbook for actually winning with AI remains daunting.
Also, consider a recent IDC Cloud and AI Adoption Survey[1] in which more than 80% of respondents said they plan to move, or repatriate, data and workloads from public cloud environments to private clouds or on-premises locations over the next year, as the initial expectations of a single public cloud provider were not realized. These dynamics add to the confusion that every CEO, CIO, CTO, and CDO faces on a daily basis.
Tomi Engdahl says:
Microsoft acquires Lobe, a drag-and-drop AI tool
https://techcrunch.com/2018/09/13/microsoft-acquires-lobe-a-drag-and-drop-ai-tool/?sr_share=facebook&utm_source=tcfbpage
Tomi Engdahl says:
Glow
Tool
https://facebook.ai/developers/tools/glow
Glow is a machine learning compiler that accelerates the performance of deep learning frameworks on different hardware platforms. It enables the ecosystem of hardware developers and researchers to focus on building next gen hardware accelerators that can be supported by deep learning frameworks like PyTorch.
Tomi Engdahl says:
Nvidia launches the Tesla T4, its fastest data center inferencing platform yet
https://techcrunch.com/2018/09/12/nvidia-launches-the-tesla-t4-its-fastest-data-center-inferencing-platform-yet/?utm_source=tcfbpage&sr_share=facebook
Nvidia today announced its new GPU for machine learning and inferencing in the data center.
Google, Nvidia said, will be among the first to bring the new T4 GPUs to its Cloud Platform.
Nvidia argues that the T4s are significantly faster than the P4s. For language inferencing, for example, the T4 is 34 times faster than using a CPU and more than 3.5 times faster than the P4.
Tomi Engdahl says:
Facebook Starts “Fact Checking” Photos And Videos Using AI
https://www.zerohedge.com/news/2018-09-13/facebook-starts-fact-checking-photos-and-videos-using-ai
Facebook on Thursday announced the expansion of their fact-checking army to send “photos and videos to all of our 27 partners in 17 countries around the world,” after using an artificial intelligence which will use “various engagement signals, including feedback from people on Facebook, to identify potentially false content.”
The company says that because people share millions of photos and videos on Facebook each day, it creates an “easy opportunity for manipulation by bad actors.”
Tomi Engdahl says:
Nellie Bowles / New York Times:
A look at Standard Cognition’s tech, which uses cameras and AI to track who people are and what they buy, as it opens San Francisco’s first cashierless store
Stealing From a Cashierless Store (Without You, or the Cameras, Knowing It)
https://www.nytimes.com/2018/09/13/technology/standard-market-retail-automation-behavioral-data.html
A start-up uses visual tracking and behavioral data to operate a new San Francisco market, which lets shoppers walk out unimpeded. And sometimes mischarged.
Tomi Engdahl says:
Khari Johnson / VentureBeat:
Nvidia says it has launched Project Maglev, an initiative to use its Drive AI platform to enable product development in industries like robotics and health care
How Nvidia is using its autonomous car platform to drive into health care
https://venturebeat.com/2018/09/13/how-nvidia-is-using-its-autonomous-car-platform-to-drive-into-health-care/
Nvidia is using the underlying architecture of its Drive autonomous vehicle platform to enable product development in other verticals with AI systems that deal with vast amounts of critical data, such as video surveillance, robotics, and health care.
Called Project Maglev, the initiative to transfer the data framework to industries beyond autonomous vehicles started roughly 18 months ago, Nvidia VP of AI infrastructure Clément Farabet told VentureBeat in a phone interview.
Tomi Engdahl says:
Is Your AI SoC Secure?
Where security is needed in AI environments.
https://semiengineering.com/is-your-ai-soc-secure/
As artificial intelligence (AI) enters every application, from IoT to automotive, it is bringing new waves of innovation and business models, along with the need for high-grade security. Hackers try to exploit vulnerabilities at all levels of the system, from the system-on-chip (SoC) up. Therefore, security needs to be integral in the AI process. The protection of AI systems, their data, and their communications is critical for users’ safety and privacy, as well as for protecting businesses’ investments. This article describes where security is needed throughout AI environments as well as implementation options for ensuring a robust, secure system.
Tomi Engdahl says:
Is AI being over-hyped in the security industry?
By Pascal Geenens 2018-09-11T15:30:37ZSecurity
https://www.itproportal.com/features/is-ai-being-over-hyped-in-the-security-industry/
Artificial intelligence won’t be replacing trained cybersecurity specialists any time soon.
Tomi Engdahl says:
https://www.uusiteknologia.fi/2018/09/12/neuromorfinen-piiri-biologiasta-mallia/
Tomi Engdahl says:
AI Has a Long Way to Go
https://www.eetimes.com/document.asp?doc_id=1333708
The 18th annual EmTech Conference opened yesterday on the MIT campus. A major focus of this conference was artificial intelligence (AI) and robotics, with attendees hearing about the great strides that AI (and software in general) will change the way that we live and work. While we can certainly see that coming, there are many jobs — even assembly-line jobs — that are still far too complex for machines. Even so, we’re seeing ethical issues that will haunt us.
Ethical issues have arisen not only because of technologies such as AI but from simply having technologies like the internet, mobile phones, and social media.
Tomi Engdahl says:
Nvidia Going All Robot, All the Time
https://www.eetimes.com/document.asp?doc_id=1333734
Most AI platform suppliers have been obsessed lately with autonomous vehicles. This week, Nvidia escalated the obsession by spreading the epidemic to “autonomous machines.”
At Nvidia’s GPU Technology Conference held here, CEO Jensen Huang wound up and pitched Nvidia AGX, a series of embedded AI high-performance computers built around Nvidia’s new Xavier processors, for a host of robotic and autonomous machines.
Phil Magney, founder and principal advisor at VSI Labs, called Nvidia “shrewd” to extend the reach of the architecture, since most competitors are focusing exclusively on automated cars. “As we know, there are lots of human driven machines out there where removing the operator is the goal. Nvidia’s new partners in Japan have their bases covered with these announcements.”
Tomi Engdahl says:
Facebook Builds Chip Team, ASIC
Web giant rallies support for AI compiler
https://www.eetimes.com/document.asp?doc_id=1333716
A Facebook executive confirmed reports that the social networking giant is hiring chip engineers and designing at least one ASIC. The news came at the @Scale event here, where Facebook announced that five chip companies will support Glow, an open-source, deep-learning compiler that it backs.
Facebook “is absolutely bringing up a silicon team focused on working with silicon providers, and we have a chip we’re building, but it’s not our primary focus,” said Jason Taylor, vice president of infrastructure at Facebook. The chip is “not the equivalent of [Google’s] TPU” deep-learning accelerator, he added, declining to provide further details on its focus or time frame.
Working with the estimated 50 companies designing AI accelerators is one focus for the new Facebook chip group. “There will be a lot of [accelerator] chips in the market,” said Taylor at a press roundtable. “The big question is whether the workloads they are designed for are the important ones at the time.”
Tomi Engdahl says:
Qualcomm’s AI solutions are powering today’s mobile, IoT and automotive experiences
https://www.eetimes.com/document.asp?doc_id=1333704
Artificial intelligence (AI) used to be the stuff of science fiction, with stories telling how AI will soon learn, react to and even understand human speech fluently. Large corporations such as Google and Amazon have created deep-learning AI systems to intelligently target ads, learn about users, understand human speech and even sound like a human.
Complexities of artificial intelligence
Computers are fantastic when it comes to data crunching; high-speed processors and linear programming allow designers to list out their desired instructions in a logical manner and have them executed quickly. However, the problems with standard programming techniques soon become revealed as programs become more complex.
Tomi Engdahl says:
https://www.uusiteknologia.fi/2018/09/20/tekoalyyn-uusi-tyokalu-avoimeen-lahdekoodiin/
IBM:n tutkimuskeskus julkaisee avoimen lähdekoodin yhteisöille uudenlaisen tekoälyn hyödyntämistä helpottavan AI Fairness 360 -työkalun.
Tomi Engdahl says:
GPGPUs Put Machine Learning on the Fast Track
https://www.electronicdesign.com/automotive/gpgpus-put-machine-learning-fast-track?Issue=ED-004_20180920_ED-004_502&sfvc4enews=42&cl=article_2_b&utm_rid=CPG05000002750211&utm_campaign=20059&utm_medium=email&elq2=7b2ab861314843cfb5d24bbf58efbaf6
NVIDIA’s AGX line of AI-augmented GPGPUs targets machine-learning applications from self-driving cars to medical instruments.
NVIDIA’s support for machine learning using GPGPUs has been extensive. Its latest Turing architecture-based GPU, the RTX 8000, combines ray-tracing support with machine-learning (ML) acceleration. The Turing architecture includes Tensor Cores to accelerate ML applications.
NVIDIA’s T4 Tensor Core GPU, built on the Turing architecture with its Tensor Core support, targets hyperscale deployment where high-performance interference is needed (Fig. 1). The PCI Express (PCIe) card only needs 75 W. Its small form factor allows for very dense system design.
Tomi Engdahl says:
Teaching Machines ‘Fairness’
https://www.eetimes.com/document.asp?doc_id=1333748
Teaching anyone about “fairness” is a laudable goal.
As humans, we may not necessarily agree on what’s fair. It sometimes depends on the context. Teaching kids to be fair — both at home and in school — is fundamental, but it’s easier said than done. With this in mind, how can we, as a society, communicate the nuances of “being fair” to artificial intelligence (AI) systems?
A team of researchers at IBM Research is taking the first crack at this conundrum. IBM is rolling out a tool kit for developers called “AI Fairness 360.” As part of this effort, IBM is offering businesses a new “cloud-based, bias-detection, and mitigation service” that corporations can use to test and verify how AI-driven systems are behaving.
Introducing AI Fairness 360
https://www.ibm.com/blogs/research/2018/09/ai-fairness-360/
Tomi Engdahl says:
Nvidia Going All Robot, All the Time
https://www.eetimes.com/document.asp?doc_id=1333734
Tomi Engdahl says:
Is Machine Learning at Google Falling Apart? Google’s System Doesn’t Believe I‘m a Person.
https://medium.com/@david.liedle/is-machine-learning-at-google-falling-apart-googles-system-doesn-t-believe-i-m-a-person-88c92159c979
Thoughts here are my own, and are not related to my employer.
But there’s one aspect of Google’s services that have become so acutely painful and disruptive to my daily life that I have to call it out:
Machine Learning for consumer-facing products at Google is out of control.
Think your Google+ profile doesn’t matter? So did I, until I realized that getting my profile suspended means I’m no longer a PERSON
When I realized even my Gmail presence was affected…
That’s right, the UI in Google+ warns you that you need to remove any spam posts before submitting for review. The problem? My profile doesn’t exist anymore. I can’t check it. I’m just… gone
Tomi Engdahl says:
Optimizing power efficiency to bring AI to the end device
https://www.eetimes.com/document.asp?doc_id=1333646
Artificial intelligence (AI) is core to making our devices smarter. With billions of connected devices, the only way to manage the tremendous amount of data created by all of these interconnections is for devices to be able to make decisions at some level independently of the cloud.
Tomi Engdahl says:
https://www.kauppakamarilehti.fi/index.php/yritykset/risto-siilasmaa-kukaan-ei-ole-liian-vanha-tai-tyhma-ymmartamaan-koneoppimista/
Tomi Engdahl says:
What is Artificial Intelligence?
Machine Learning and Deep Learning
https://aws.amazon.com/machine-learning/what-is-ai/
Tomi Engdahl says:
https://www.elementsofai.com
Tomi Engdahl says:
Facebook’s new ‘SapFix’ AI automatically debugs your code
https://techcrunch.com/2018/09/13/facebook-sapfix-debugger/