Experts have made it clear that artificial intelligence will soon impact all industries, and at a CES panel on “AI — All Industry Integration,” moderated by Future PLC global editor-in-chief Bill Gannon, three experts teased out what that means for chatbots, computers, smartphones and automotive. All three noted some of the common challenges, including the need to change current business models, proactively provide mechanisms for users to guard their data and find ways to cope with the unforeseen going forward. Continue reading CES Panel Discusses the Industries That Are Integrating AI

A conference on “Robots for Good” sought to allay increased fears that robot overlords will soon rule the world and make humans redundant in the workforce. UC Berkeley professor Ken Goldberg, who heads a robotics lab there, spoke about his “radically hopeful vision of the future.” Robots will not replace humans, he said, but rather enable people to focus on what they do best: creativity, innovation, empathy and other inherent human traits. Goldberg also put the fear of robots in historical perspective. Continue reading CES 2020: ‘Robots for Good’ Advocates See Hopeful Future

Intel acquired Israel-based AI chip manufacturer Habana Labs for about $2 billion, to strengthen its offerings for data centers requiring such chips. The tech giant already stated that it expects to complete more than $3.5 billion in sales related to artificial intelligence, an increase of 20 percent from last year. The Habana purchase is just one of several that Intel has made in recent years in its efforts to grow new markets. Intel expects the AI chip market to grow to $25 billion by 2024, half from selling chips for data centers. Continue reading Intel Doubles Down on AI with $2 Billion Habana Acquisition

We’re not going to lie: the annual “heads up CES” piece on artificial intelligence is a major exercise in hit or miss. This is because technology rarely evolves on an annual time scale, and certainly not advanced technology like AI. Yet, here we are once again. Sure, 2019 was as fruitful as it gets in the AI research community. The raw debate between Neural Networks Extremists (those pushing for an “all neural nets all the time” approach to intelligence) and the Fanatical Symbolists (those advocating a more hybrid approach between knowledge bases, expert systems and neural nets) took an ugly “Mean Girl” turn, with two of the titans of the field (Gary Marcus and Yann LeCun) trading real insults on Twitter just a few days ago.  Continue reading The Human Interface: What We Expect From AI at CES 2020

Amazon introduced Contact Lens for Amazon Connect and Amazon Kendra, two AI-enabled tools to help enterprise customers gain more information from data found in multiple sources. Both services, available for preview now on Amazon Web Services, assist cloud customers in incorporating natural language processing in a timely fashion. According to Amazon, Contact Lens for Amazon Connect and Amazon Kendra’s functionality are based on the integration of machine learning. Both services are plug-and-play. Continue reading Amazon Web Services Unveils AI Tools for Enterprise Clients

Microsoft’s CTO office is reportedly creating a Data Dignity team to find ways to give users more control over their personal information — including the possibility of buying and selling it to third-parties. To set itself apart from other tech behemoths, Microsoft has been asserting its efforts for consumer privacy. But the company has faced its own privacy faux pas such as collecting data for Windows 10 and using human workers to transcribe Skype conversations. Data Dignity could help burnish its image. Continue reading Microsoft Develops Data Dignity Project to Empower Users

Los Altos, CA-based startup Cerebras, dedicated to advancing deep learning, has created a computer chip almost nine inches (22 centimeters) on each side — huge by the standards of today’s chips, which are typically the size of postage stamps or smaller. The company plans to offer this chip to tech companies to help them improve artificial intelligence at a faster clip. The Cerebras Wafer-Scale Engine (WSE), which took three years to develop, has impressive stats: 1.2 trillion transistors, 46,225 square millimeters, 18 gigabytes of on-chip memory and 400,000 processing cores. Continue reading Cerebras Builds Enormous Chip to Advance Deep Learning

Researchers recently introduced a series of rigorous benchmark tasks that measure the performance of sophisticated language-understanding AI. Facebook AI Research with Google’s DeepMind, University of Washington and New York University introduced SuperGLUE last week, based on the idea that deep learning models for today’s conversational AI require greater challenges. SuperGLUE, which uses Google’s BERT representational model as a performance baseline, follows the 2018 introduction of GLUE (General Language Understanding Evaluation), and encourages the creation of models that can understand more nuanced, complex language. Continue reading SuperGLUE Is Benchmark For Language-Understanding AI

Intel, which is in development on its Loihi “neuromorphic” deep-learning chips, just debuted Pohoiki Beach, code name for a new system comprised of 64 Loihi chips and eight million “neurons.” Loihi’s neuromorphism denotes the fact that it is modeled after the human brain, and Pohoiki Beach is capable of running AI algorithms up to 1,000 faster and 10,000 times more efficiently than the typical CPU. Applications could include everything from autonomous vehicles to electronic robot skin and prosthetic limbs. Continue reading Intel Debuts 64-Chip Neuromorphic System for AI Algorithms

Amazon, which launched its new StyleSnap feature to select iOS and Android users in April, will soon make the in-app tool widely available, said company worldwide consumer head Jeff Wilke at the company’s re:MARS AI conference in Las Vegas. Users can reach StyleSnap via a shortcut found by tapping the camera icon in the Amazon app’s upper right-hand corner. Based on image recognition, the machine learning-enabled StyleSnap (and Pinterest Lens competitor) will offer similar items to any photo or screenshot uploaded by a user. The algorithms also incorporate computer vision and deep learning. Continue reading Amazon’s AI-Enabled StyleSnap Is Ideal for Fashion Market

At this week’s annual Facebook F8 developer conference in San Jose, California, company CTO Mike Schroepfer discussed the progress being made by internal teams dedicated to reducing the spread of misinformation, hate speech, and abuse on the social platform using various artificial intelligence techniques. In the course of a single quarter, according to Schroepfer, Facebook takes down more than a billion “spammy” accounts, more than 700 million fake accounts, and tens of millions of items containing violent content or nudity.

Continue reading Facebook Using Artificial Intelligence to Reduce Bias/Abuse

Amazon introduced AWS Deep Learning Containers, a collection of Docker images preinstalled with preferred deep learning frameworks, with the aim of making it more seamless to get AI-enabled apps on Amazon Web Services. At AWS, general manager of deep learning Dr. Matt Wood noted that the company has “done all the hard work of building, compiling, and generating, configuring, optimizing all of these frameworks,” taking that burden off of app developers. The container images are all “preconfigured and validated by Amazon.” Continue reading AWS Tool Aims to Simplify the Creation of AI-Powered Apps

Nvidia made a number of compelling announcements at this week’s GPU Technology Conference (GTC 2019) in San Jose, California. The company unveiled its GauGAN AI image creator that uses generative adversarial networks (GANs) to turn sketches into nearly photorealistic images. As part of its cloud pursuits, the company unveiled its latest RTX server configuration that is designed for Hollywood studios and those who want to create visual content quickly (each server pod can support up to 1,280 GPUs). Nvidia also announced partnerships with 3D software makers including Adobe, Autodesk and Unity to integrate Nvidia’s RTX ray-tracing platform. Continue reading Nvidia Demos New Products at Deep Learning & AI Confab

Google has unveiled GPipe, an open-sourced library that makes training deep neural networks more efficient under the TensorFlow framework Lingvo for sequence modeling. According to Google AI software engineer Yanping Huang, “in GPipe … we demonstrate the use of pipeline parallelism to scale up DNN training,” noting that larger DNN models “lead to better task performance.” Huang and his colleagues published a paper on “Efficient Training of Giant Neural Networks Using Pipeline Parallelism.” Continue reading Google GPipe Library Speeds Deep Neural Network Training

Gartner just released its 2019 CIO Survey of 3,000+ executives in 89 countries, which found that implementation of artificial intelligence grew 270 percent in the past four years. In 2018, use of AI grew 37 percent, up from 10 percent in 2015. The company estimates that the AI market will be valued at $6.14 billion by 2022. Gartner distinguished research vice president Chris Howard noted that we are still “far from general AI that can wholly take over complex tasks,” but that we have entered the “augmented intelligence” era. Continue reading Gartner Report Shows Dramatic Growth in Enterprise AI Use