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://github.com/Microsoft/EdgeML
Tomi Engdahl says:
Daniel Oberhaus / Motherboard:
Researchers warn so-called “perceptual” ad blockers, which aim to visually recognize ads on a page to block them, are ineffective and create new attack vectors — Perceptual ad blockers will come out on the losing side in the war against internet advertisers and expose users …
Researchers Defeat Most Powerful Ad Blockers, Declare a ‘New Arms Race’
https://motherboard.vice.com/en_us/article/xwjzka/researchers-defeat-most-powerful-ad-blockers-declare-a-new-arms-race
Last year, Princeton researchers created a perceptual ad blocker, which could visually locate advertisements on a webpage and filter them out. This plugin was supposed to be the “ad blocking superweapon” that would put an end to the ad-blocking arms race since it didn’t target ads based on their code, but on the way they looked on the page.
According to new research published this week on arXiv, however, an AI was able to defeat perceptual ad blockers. Moreover, the researchers warned, ad blockers will be on the losing side of the arms race and expose their users to new attack vectors in the process.
Tomi Engdahl says:
Will Knight / MIT Technology Review:
Andrew Moore, Google Cloud’s new head of AI, on mistakes companies make in adopting AI, working with US military, and China’s importance to Google’s AI plans
AI is not “magic dust” for your company, says Google’s Cloud AI boss
https://www.technologyreview.com/s/612394/ai-is-not-magic-dust-for-your-company-says-googles-cloud-ai-boss/
Andrew Moore says getting the technology to work in businesses is a huge challenge.
Tomi Engdahl says:
Eye eye! AI could stop blindness, Facebook’s after math, and how to get started in the ML biz
The week’s other news in machine learning
https://www.theregister.co.uk/2018/11/10/ai_roundup_101118/
Floating point maths for AI chips: Facebook has published code that improves the efficiency of number crunching to train and deploy neural networks using AI chips.
There’s a ton of matrix maths that’s performed when you feed a neural network data to train it to perform a specific function, whether its a natural language processing or computer vision tasks. During the training process, all the numbers are encoded using floating point and then rounded up or down to a quantized figure so they can be deployed more quickly.
Developers at Facebook have crafted new techniques to make all the maths in Floating Point 16 more efficient so that they don’t have to be quantized for neural networks to be deployed.
Using software tricks to save on compute will be future as hardware limitations begin to creep in.
You, too, can become an RL whiz: OpenAI has released a range of resources to help those interested in breaking into the world of reinforcement learning.
The guide, dubbed Spinning Up in Deep RL, is made up of a document introducing the basic theory around RL and the algorithms commonly used in research.
“Spinning Up in Deep RL is part of a new education initiative at OpenAI which we’re ‘spinning up’ to ensure we fulfill one of the tenets of the OpenAI Charter: ‘Seek to create a global community working together to address AGI’s global challenges,’” the research institute said this week.
Welcome to Spinning Up in Deep RL!
https://spinningup.openai.com/en/latest/index.html
Tomi Engdahl says:
Artificial Intelligence, Real Concerns: Hype, Hope and the Hard Truth About AI
https://securityintelligence.com/artificial-intelligence-real-concerns-hype-hope-and-the-hard-truth-about-ai/
Tomi Engdahl says:
Clive Thompson / Wired:
AI needs to be taught everyday common sense, not just pattern recognition, to overcome the limits of deep learning and produce safer, more useful devices — FIVE YEARS AGO, the coders at DeepMind, a London-based artificial intelligence company, watched excitedly as an AI taught itself to play a classic arcade game.
https://www.wired.com/story/how-to-teach-artificial-intelligence-common-sense/
Tomi Engdahl says:
Andrew Tarantola / Engadget:
Intel unveils Neural Compute Stick 2 for developing AI algorithms and computer vision systems locally using its Movidius Myriad X AI chip, for $100 — Ahead of its first AI developers conference in Beijing, Intel has announced it’s making the process of imparting intelligence into smart home gadgets …
https://www.engadget.com/2018/11/14/intel-neural-compute-stick-2/
Tomi Engdahl says:
How machine learning systems sometimes surprise us
https://techcrunch.com/2018/11/13/how-machine-learning-systems-sometimes-surprise-us/?sr_share=facebook&utm_source=tcfbpage
This simple spreadsheet of machine learning foibles may not look like much but it’s a fascinating exploration of how machines “think.” The list, compiled by researcher Victoria Krakovna, describes various situations in which robots followed the spirit and the letter of the law at the same time.
Tomi Engdahl says:
AI Trying To Design Inspirational Posters Goes Horribly And Hilariously Wrong
https://www.iflscience.com/technology/ai-trying-to-design-inspirational-posters-goes-horribly-and-hilariously-wrong/
Whenever an artificial intelligence (AI) does something well, we’re simultaneously impressed as we are worried. AlphaGO is a great example of this: a machine learning system that is better than any human at one of the world’s most complex games. Or what about Google’s neural networks that are able to create their own AIs autonomously?
we feel such glee when an AI goes a little awry.
Now, a new AI has appeared on the wilderness of the Web, and it goes by the name InspiroBot. As you might expect, it designs “Inspirational Posters” for you
http://inspirobot.me
Tomi Engdahl says:
A VC View Of The AI Landscape
https://semiengineering.com/a-vc-view-of-the-ai-landscape/
Amid a dramatic increase in investment, chip startups see opportunities to change the AI ecosystem.
In this blog post, I’ll highlight my takeaways from the recent AI Hardware Summit where I participated as a panelist. The conference’s focus on developing hardware accelerators for neural networks and computer vision attracted companies from across the ecosystem – AI chip startups, semiconductor companies, system vendors/OEMs, data center providers, financial services companies and VCs, which is where I fit in as an Investment Principal at Applied Ventures (the VC arm of Applied Materials). While AI is still coming of age, it was clear from the conference that the AI developer community is rapidly growing, offering a wide range of investment opportunities.
Tomi Engdahl says:
Smart Manufacturing
https://semiengineering.com/smart-manufacturing/
How to utilize manufacturing data and AI/ML to improve efficiency and yield.
Tom Salmon, vice president of collaborative technology platforms at SEMI, talks about smart manufacturing, and the role of AI, smart gateways, and digital twins.
https://www.youtube.com/watch?v=e9DQ_Xfc2K0
Tomi Engdahl says:
Machine Learning Based Prediction: Health Behavior on BP
https://semiengineering.com/machine-learning-based-prediction-health-behavior-on-bp/
ML algorithm + individual data = personalized recommendations to reduce blood pressure
Tomi Engdahl says:
Machine Learning Moves Into Fab And Mask Shop
https://semiengineering.com/machine-learning-moves-into-fab-and-mask-shop/
Experts at the Table, part 2: Where can this technology be applied, why it is taking so long, and what challenges lie ahead.
Tomi Engdahl says:
EE Times Silicon 60: The Rise of Machine Learning
https://www.eetimes.com/document.asp?doc_id=1333984
EE Times’ 19th revision of the Silicon 60, our annual list of startups to watch, documents the definitive rise of machine learning as a form of hardware-supported computing. The development atmosphere is feverish, and the technology market has the same air of dynamic, fast-paced change that it had when the first microprocessors launched in the 1970s.
Of course, the Silicon 60 is broader than machine learning. This year’s profiled startups are working on silicon and compound semiconductor manufacturing; conductive materials and metamaterials; analog and digital ICs and systems-on-chip (SoCs); memory; field-programmable gate array (FPGA) fabrics; gallium nitride for power and lighting; energy harvesting; sub-threshold-voltage operation of ICs; signal-processing techniques; 5G communications for automobiles and the internet of things (IoT); LiDAR; wireless power transfer; environmental sensors; microelectromechanical system (MEMS) design and manufacturing; cloud-based EDA; organic LED and micro-LED displays; neural networks; and other architectures for machine learning, vision, and cognitive processing.
Tomi Engdahl says:
Baidu Backs Swiss Neuromorphic Intelligence Chip Developer
https://www.eetimes.com/document.asp?doc_id=1333983
Swiss startup aiCTX has closed a $1.5 million pre-A funding round from Baidu Ventures to develop commercial applications for its low-power neuromorphic computing and processor designs and enable what it calls “neuromorphic intelligence.” It is targeting low-power edge-computing embedded sensory processing systems.
Tomi Engdahl says:
New Architectures Bringing AI to the Edge
https://www.eetimes.com/document.asp?doc_id=1333920
As artificial intelligence (AI) capability moves from the cloud to edge, it is inevitable that chipmakers will find ways to implement AI functions like neural-network processing and voice recognition in smaller, more efficient, and cost-effective devices.
The big, expensive AI accelerators that perform tasks back in the data center aren’t going to cut it for edge node devices. Battle lines are being drawn among various devices — including CPUs, GPUs, FPGAs, DSPs, and even microcontrollers — to implement AI at the edge with the required footprint, price point, and power efficiency for given applications.
To that end, a pair of intriguing architectures created specifically for implementing AI at the edge are being introduced at the Linley Processor Conference on Tuesday by Cadence Design Systems and Flex Logix Technologies. Both focus on bringing AI functionality into edge node devices with an emphasis on reducing the memory footprint.
Tomi Engdahl says:
Who’s Who in AI SoCs
https://www.eetimes.com/document.asp?doc_id=1333923
Tomi Engdahl says:
AI Edges to Factory Floor
https://www.eetimes.com/document.asp?doc_id=1333973
Deep neural networks are crawling toward the factory floor.
For several early adopters, neural nets are the new intelligence embedded behind the eyes of computer-vision cameras. Ultimately, the networks will snake their way into robotic arms, sensor gateways, and controllers, transforming industrial automation. But the change is coming slowly.
“We’re still in the early phases of what’s likely to be a multi-decade era of advances and next-generation machine learning algorithms, but I think we’ll see enormous progress in the next few years,” said Rob High, chief technology officer for IBM Watson.
Neural networks will nest in growing numbers of Linux-capable, multicore x86 gateways and controllers appearing on and around the factory floor. Emerging 5G cellular networks will one day give neural nets ready access to remote data centers, said High.
Tomi Engdahl says:
Data on digitalisaation ja tekoälyn perusta
https://www.tivi.fi/Kumppaniblogit/elisa_oyj/data-on-digitalisaation-ja-tekoalyn-perusta-6748970
Kaikesta datasta on tullut digitalisaation ansiosta arvokasta. Yksikään yritys ei voi tänään tietää, mille datalla tulevaisuudessa on käyttöä ja mille ei. Siksi kaikessa toiminnassa lähtökohtana kannattaa pitää sitä, että älä koskaan tuhoa mitään dataa.
Data on se perusta, jolle kaikki yritykset rakentavat digitalisaation ja tekoälyn hankkeitaan. Hyvän datan päälle rakennettu keskinkertainenkin tekoälysovellus tuo hyviä liiketoiminnallisia tuloksia, mutta huonon datan päälle rakennettu maailman paraskaan tekoäly ei saa aikaan hyviä tuloksia.
Tomi Engdahl says:
The Future of Military (Artificial) Intelligence
https://www.designnews.com/electronics-test/future-military-artificial-intelligence/165978317459765?ADTRK=UBM&elq_mid=6534&elq_cid=876648
In a free webinar, AI, military, and law enforcement experts spoke with Design News about how the defense industry is using artificial intelligence in warfare and beyond and what the future may hold.
When President Trump approved the National Defense Authorization Act (NDAA) to the tune of $717 billion for the next fiscal year, he also cemented a position for artificial intelligence research in the US Department of Defense (DoD). In addition to providing funding for future AI research contracts, a portion of funds from the NDAA will go toward establishing a Joint Artificial Intelligence Center (JAIC) under the DoD to oversee about 600 active AI projects. A National Security Commission on Artificial Intelligence will also be given a $10 million budget to examine how AI can be leveraged for national security.
While the military has spent decades researching artificial intelligence, the proliferation of the technology and concerns over the US maintaining its position as a leader in the AI space have led to more serious efforts for the defense industry to partner with Silicon Valley to develop AI technologies.
But the relationship between the defense sector and Silicon Valley is not as easy and happy of a marriage as some might expect. There also is tension within major companies, such as Google and Microsoft, about developing AI technologies for military purposes.
Tomi Engdahl says:
http://www.etn.fi/index.php/13-news/8726-ita-suomen-yliopiston-tekoalytutkimus-sai-rahaa
Tomi Engdahl says:
Google accused of ‘trust demolition’ over health app
https://www.bbc.com/news/technology-46206677
A controversial health app developed by artificial intelligence firm DeepMind will be taken over by Google, it has been revealed.
Streams was first used to send alerts in a London hospital but hit headlines for gathering data on 1.6 million patients without informing them.
DeepMind now wants the app to become an AI assistant for nurses and doctors around the world.
One expert described the move as “trust demolition”.
Google ‘betrays patient trust’ with DeepMind Health move
https://www.theguardian.com/technology/2018/nov/14/google-betrays-patient-trust-deepmind-healthcare-move
Moving healthcare subsidiary into main company breaks pledge that ‘data will not be connected to Google accounts’
Google has been accused of breaking promises to patients, after the company announced it would be moving a healthcare-focused subsidiary, DeepMind Health, into the main arm of the organisation.
The restructure, critics argue, breaks a pledge DeepMind made when it started working with the NHS that “data will never be connected to Google accounts or services”. The change has also resulted in the dismantling of an independent review board, created to oversee the company’s work with the healthcare sector, with Google arguing that the board was too focused on Britain to provide effective oversight for a newly global body.
Google says the restructure is necessary to allow DeepMind’s flagship health app, Streams, to scale up globally. The app, which was created to help doctors and nurses monitor patients for AKI, a severe form of kidney injury, has since grown to offer a full digital dashboard for patient records.
Tomi Engdahl says:
Cadence’s Paul McLellan shares highlights from five presentations all discussing what’s behind AI’s movement to edge devices, the vast amount of investment going into the area, and where a few of the foreseeable challenges lie.
Bagels and Brains: SEMI’s Artificial Intelligence Breakfast
https://community.cadence.com/cadence_blogs_8/b/breakfast-bytes/posts/semi18-ai
Tomi Engdahl says:
Tom Simonite / Wired:
As AI-building frameworks get open-sourced, DIY tinkerers use them for tasks like identifying plant diseases, automating dry-cleaning, making art, and more
The DIY Tinkerers Harnessing the Power of Artificial Intelligence
https://www.wired.com/story/diy-tinkerers-artificial-intelligence-smart-tech/
Tomi Engdahl says:
James Vincent / The Verge:
Amazon is using “neural text-to-speech” (NTTS) tech to develop new speaking styles for Alexa, will launch a newscaster style to read articles in a few weeks
Alexa will soon be able to read the news just like a professional
https://www.theverge.com/2018/11/20/18104413/amazon-alexa-speaking-style-machine-learning-neural-ntts-newscaster
Amazon is using AI to develop new speaking styles for Alexa, including a newscaster voice for reading articles
Tomi Engdahl says:
A Hardware Chip Aids Tensor Machine Learning Software Applications
Google’s tensor processing unit has the potential to do more in n-multidimensional mathematics.
https://www.designnews.com/electronics-test/hardware-chip-aids-tensor-machine-learning-software-applications/197758117459777?ADTRK=UBM&elq_mid=6592&elq_cid=876648
As machine learning is being applied to data-intensive applications, such as Internet search, natural language processing (NLP), and image recognition, Moore’s Law is expediently plateauing. The central processing unit (CPU) that provided the computational process for today’s computing machines is unable to meet the demands of “n-multidimensional” datasets.
The CPU/Microprocessor
Machine learning applications, such as linear regression and convolutional neural networks (CNN), can be performed on a CPU. The serial and linear processing operations are limited by the CPU’s handling of n-multidimensional datasets.
The GPU
The graphical processing unit (GPU) is the next computational evolutionary step in processing capability. Unlike the CPU or microprocessor, the GPU is designed to rapidly alter and manipulate memory for the acceleration of images.
GPUs can perform matrix operations simultaneously as compared to a CPU. Therefore, a GPU is a parallel processing device. Although the GPU’s computational capabilities are faster than those of a CPU because of the parallel processing feature, the GPU is unable to perform n-multidimensional computations.
The TPU
The introduction of a tensor processing unit (TPU) occurred at Google’s Mountain View, California I/O conference in 2016.
It is an application-specific integrated circuit (ASIC) that has the potential to do more in n-multidimensional mathematics.
A n-multidimensional array, known as a Tensor, is at the core of machine learning algorithms. A tensor can be a single input (a scalar), a vector (multiple inputs), or a matrix of inputs. Google’s TensorFlow is a workflow that allows training, testing, and production deployment of machine learning applications. With the use of TensorFlow, TPUs can be managed to provide an order of magnitude of performance per watt for machine learning through better optimization techniques. These optimization techniques are based in calculus mathematics.
Tomi Engdahl says:
2 Big Shifts, Lots Of Questions
https://semiengineering.com/2-big-shifts-lots-of-questions/
Why AI, and systems companies designing their own chips, could alter semiconductor manufacturing.
Tomi Engdahl says:
U.S. Mulls Curbs on Artificial Intelligence Exports
https://www.securityweek.com/us-mulls-curbs-artificial-intelligence-exports
The administration of US President Donald Trump is exploring curbing exports of sensitive technologies including artificial intelligence for national security reasons, according to a proposal this week.
The proposal to control sales of certain technologies “essential to the national security of the United States” comes amid growing trade friction with Beijing — and fears that China may overtake the US in some areas such as artificial intelligence.
Tomi Engdahl says:
Tekoäly vauhdittaa Venäjän infosotaa länttä vastaan
https://www.verkkouutiset.fi/tekoaly-vauhdittaa-venajan-infosotaa-lantta-vastaan/
Tutkija varoittaa lännen tulevan yllätetyksi, ellei uuden uhan vakavuuteen reagoida ajoissa.
Venäjän vaikuttamisoperaatiot läntisten demokratioiden horjuttamiseksi eivät osoita laantumisen merkkejä. On olemassa vahvoja viitteitä siitä, että tekoälystä on jo lähiaikoina muodostumassa Kremlin ohjaaman informaatiosodankäynnin uusi ja tärkeä väline, amerikkalaisen Brookings Institution -tutkimuslaitoksen tutkija, tohtori Alina Polyakova arvioi.
Tomi Engdahl says:
https://www.uusiteknologia.fi/2018/11/21/huawei-hakee-lisaa-kehittajia-hiai-2-0-tekoalyalustalleen/
Tomi Engdahl says:
http://www.etn.fi/index.php/13-news/8745-huawei-avaa-tekoalyalustansa-kehittajille
Tomi Engdahl says:
Are Killer Robots the Future of War? Parsing the Facts on Autonomous Weapons
https://www.nytimes.com/2018/11/15/magazine/autonomous-robots-weapons.html
Tomi Engdahl says:
AI Trying To Design Inspirational Posters Goes Horribly And Hilariously Wrong
https://www.iflscience.com/technology/ai-trying-to-design-inspirational-posters-goes-horribly-and-hilariously-wrong/
http://inspirobot.me
Tomi Engdahl says:
The Trouble With Trusting AI to Interpret Police Body-Cam Video
https://spectrum.ieee.org/computing/software/the-trouble-with-trusting-ai-to-interpret-police-bodycam-video
Axon claims that it will train its AI system using its existing trove of body-camera data—currently standing at 30 petabytes of video, collected by 200,000 officers. The system will then be able to redact the video to protect people’s privacy, interpret and describe in written form the recorded events, and eventually help generate police reports from those descriptions. Such automated tools would free police officers to perform more valuable tasks, and they would create a searchable database of police interactions with the public. Axon has also filed a patent for real-time face recognition, which a number of its competitors are also actively developing for police body cameras.
Eliminating tedious paperwork by automatically classifying who is doing what, where, and with whom in body-cam footage is certainly an attractive idea. But we, along with other outside observers, caution that dangers lurk. Many of the AI capabilities that Axon proposes to deploy aren’t mature enough. And even if they were, there would be no way to tell if the technology is free from bias and other worrisome issues
Tomi Engdahl says:
Artificial intelligence, machine learning and Ubuntu
https://www.ubuntu.com/engage/ai-ml-ubuntu?utm_source=facebook_ad&utm_medium=social&utm_campaign=FY19_Cloud_K8_WBN_AIML
Tomi Engdahl says:
Quantum computing, not AI, will define our future
It’s the 21st century space race
https://techcrunch.com/2018/11/17/quantum-computing-not-ai-will-define-our-future/?sr_share=facebook&utm_source=tcfbpage
Tomi Engdahl says:
How to future-proof your IT job in the age of AI
Who’s afraid of robots? Here’s how to stay one step ahead of the competition
https://enterprisersproject.com/article/2018/11/how-future-proof-your-it-job-age-ai?sc_cid=7016000000127ECAAY
Could a robot do your job? Could you help a robot do its job? If you are thinking about your career development and where you’d like to be a year from now, it’s time to ask yourself these questions. IDC estimates that 40 percent of digital transformation initiatives in 2019 will use AI services, and by 2021, 75 percent of enterprise applications will use AI. No matter your title – from entry level to CIO – it’s wise to think about how your role and responsibilities may shift as technologies like AI, automation, and robotics evolve and get smarter.
Tomi Engdahl says:
Amazon Comprehend adds customized language lists to machine learning tool
https://techcrunch.com/2018/11/19/amazon-comprehend-adds-customized-language-lists-to-machine-learning-tool/?sr_share=facebook&utm_source=tcfbpage
Tomi Engdahl says:
https://www.uusiteknologia.fi/2018/11/23/nopeampaa-tekoalylaskentaa-muistin-avulla-vahemmalla-sahkolla/
Tomi Engdahl says:
http://www.etn.fi/index.php/13-news/8755-laskentaa-suoraan-muistissa
Tomi Engdahl says:
http://www.etn.fi/index.php/13-news/8754-maailman-ensimmainen-tekoalyyn-perustuva-ajopaivakirja
Kuopiolainen teknologiayhtiö Kiho on kehittänyt maailman ensimmäisen tekoälyyn perustuvan ajopäiväkirjan, joka oppii parissa viikossa erottamaan kuljettajan työajot vapaa-ajan ajoista. Innovaatio tehostaa paljon autoilevien ammattilaisten ajankäyttöä ja poistaa ajojen manuaaliset kirjausvaiheet.
Tomi Engdahl says:
http://www.etn.fi/index.php/13-news/8748-tekoaly-sopii-nyt-tikulle
Neural Compute Stick 2 opetettava tekoälylaite, joka sopii muistitikun tilaan. Se ei tarvitse pilven apua laskentaansa. Tämä taasen perustuu tehokkaaseen Movidius Myriad X -kuvaprosessoriin.
NCS2-tikku on ennen kaikkea kehitysalusta. Algoritmeja kehitetään OpenVINO-työkaluilla, jolla onnistuu esimerkiksi konenäkösovellusten kehittäminen.
Tomi Engdahl says:
Arm Leads Project to Develop an Armpit-Sniffing Plastic AI Chip
https://spectrum.ieee.org/tech-talk/semiconductors/processors/flexible-plastic-armpit-sniffer-chips-will-be-powered-by-machine-learning
Tomi Engdahl says:
https://www.iflscience.com/technology/ai-programmed-to-solve-zodiac-killer-mystery-creates-creepy-poetry-on-the-side/
Tomi Engdahl says:
Faster new Intel AI brain sticks into the side of your PC for $99
https://www.cnet.com/news/faster-new-intel-ai-brain-sticks-into-the-side-of-your-pc-for-99/?ftag=COS-05-10aaa0h&utm_campaign=trueAnthem%3A+Trending+Content&utm_content=5bed473104d30132ddce1d37&utm_medium=trueAnthem&utm_source=facebook
The Neural Compute Stick 2 uses a Movidius Myriad X artificial intelligence chip and is geared for prototype projects.
Tomi Engdahl says:
The Military Just Created An AI That Learned How To Program Software
https://www.futurism.com/military-created-ai-learned-to-program/
“BAYOU” scraped the internet to learn what the code behind software is supposed to do.
Tomi Engdahl says:
Liam Tung / ZDNet:
Waycare platform, using predictive analytics, data from connected cars, road cameras, and apps like Waze, helped to reduce crashes by 17% along a Nevada highway
Waze-fed AI platform helps Las Vegas cut car crashes by almost 20%
https://www.zdnet.com/article/waze-fed-ai-platform-helps-las-vegas-cut-car-crashes-by-almost-20/
Predictive analytics allow Las Vegas traffic authorities to take preventative action that reduces the risk of collisions.
An AI-led, road-safety pilot program between analytics firm Waycare and Nevada transportation agencies has helped reduce crashes along the busy I-15 in Las Vegas.
The Silicon Valley Waycare system uses data from connected cars, road cameras and apps like Waze to build an overview of a city’s roads and then shares that data with local authorities to improve road safety.
Waycare struck a deal with Google-owned Waze earlier this year
RTC reports that Waycare helped the city reduce the number of primary crashes by 17 percent along the Interstate 15 Las Vegas.
RTC claims that in areas where preventative measures were deployed 91 percent of drivers reduced their speed to below 65 MPH.
Tomi Engdahl says:
Mirai Translate Leverages Deep Learning to Perfect Language Translation
https://www.wired.com/brandlab/2018/10/mirai-translate-leverages-deep-learning-perfect-language-translation/?intcid=polar&utm_source=polar&utm_medium=nativetile
Translation software was widely considered to be “figured out” with the development of a technology known as statistical machine translation (SMT). Up until that point, language translation revolved around hard-coded grammar rules (subject goes before verb, and so on). Then SMT emerged, using statistics (logic and probability to choose words) to make translations more natural and fluid.
Now, state-of-the-art artificial intelligence can do even better. So much better, according to Dr. Mick Etoh, CEO of Tokyo-based Mirai Translate (majority-owned by NTT Docomo), that it could soon be akin to (or better than) a human translator.
Tomi Engdahl says:
Technology Startups News:
Botkeeper, which automates bookkeeping workflows through its human-assisted AI platform, raises $18M Series A led by Greycroft and Google’s Gradient Ventures
AI bookkeeping startup Botkeeper secures $18 million to grow its engineering, sales, and marketing team
http://techstartups.com/2018/11/21/ai-bookkeeping-startup-botkeeper-secures-18-million-grow-engineering-sales-marketing-team/
Tomi Engdahl says:
Jeremy Kahn / Bloomberg:
NIPS, an important conference for AI researchers, changes acronym for the event to NeurIPS after complaints the former one contributed to a sexist atmosphere — – Organizers had previously said they would stick with “NIPS” — Popular artificial-intelligence event to be known as NeurIPS
Top AI Conference Swaps Acronym After Sexism, Misconduct Protest
https://www.bloomberg.com/news/articles/2018-11-21/top-ai-conference-swaps-acronym-after-sexism-misconduct-protest
One of the world’s most important conferences for researchers working on artificial intelligence has changed the acronym used for the event following complaints the former one contributed to a sexist atmosphere.
The conference on Neural Information Processing Systems, which takes place annually in early December, had been commonly known by the acronym NIPS. The foundation that runs the conference said it will now use the acronym NeurIPS instead.