ICYMI: Battle against bias and new chips an AI game changer
New chips for artificial intelligence could be game changer
A team of researchers from the University of Pennsylvania’s School of Engineering and Applied Science, in partnership with scientists from Sandia National Laboratories and Brookhaven National Laboratory, has introduced a computing architecture specifically designed for use in artificial intelligence (AI). It is hoped the new chip will help usher in a new wave of hardware and software co-design. Until now, the AI industry has been dominated by software companies, due to the unique challenges presented by Big Data, artificial intelligence and machine learning.
Read the full story: https://aimagazine.com/articles/new-chips-for-artificial-intelligence-could-be-game-changer
Securing the future of IoT with AI biometric technology
The digital password as we know it quietly marked its 60th birthday earlier this year. Back in 1962, MIT professor Fernando Corbató came up with the system in order to allow four colleagues to access the then-new IBM 7090 in a “time-sharing” environment. For context, it would be another seven years before ARPANET – which would eventually morph into the internet and World Wide Web – was turned on. After six decades, the traditional password is in decline. Growing security risks brought about by the introduction and growth of the Internet of Things (IoT) mean a new breed of AI-powered biometric identification services is going to be needed to keep the world safe. Your first pet’s name is no longer required. Instead, expect faces, fingers and voices to be called upon more often as we navigate the new networks.
Read the full story: https://aimagazine.com/articles/securing-the-future-of-iot-with-ai-biometric-technology
MIT models mean a new life for mobile devices training AI
Researchers at MIT and the MIT-IBM Watson AI Lab have developed a technique that enables on-device training using less than a quarter of a megabyte of memory. The new approach enables artificial intelligence (AI) models to learn from new data on devices like smartphones and sensors, reducing energy costs and privacy risks. Microcontrollers power billions of connected devices but have limited memory and no operating system, which makes it difficult to train artificial intelligence models on these “edge devices”. Training a machine-learning model on an intelligent edge device allows it to adapt to new data and make better predictions, say the MIT researchers.
Read the full story: https://aimagazine.com/articles/mit-models-mean-a-new-life-for-mobile-devices-training-ai
A very human problem: The battle against bias in AI
Artificial intelligence (AI) does not have opinions. There are no baked-in beliefs it would like to champion, no self-evident propositions it's itching to share with the world. Instead, AI relies on and learns from huge datasets generated by humans. And while nobody consciously includes bias in a database, over time it has crept in. Without human intervention, AI could be reinforcing some damaging societal bias, limiting its impact as the next great technical innovation.
Read the full story: https://aimagazine.com/articles/a-very-human-problem-the-battle-against-bias-in-ai
AI predicts human game player actions with 80% accuracy
Researchers in the United States have developed a new set of algorithms which predict volleyball players’ in-game actions with more than 80% accuracy, opening up a wealth of new opportunities for human-machine interaction. The new algorithms developed in Cornell University’s Laboratory for Intelligent Systems and Controls combine visual data with information that is more implicit, which might include an athlete’s specific role on the team. The lab is now collaborating with the university’s Big Red hockey team to expand the research project’s applications.
Read the full story: https://aimagazine.com/articles/ai-predicts-human-game-player-actions-with-80-accuracy
Warehouse robotics market to grow by over US$4bn by 2026
The global warehouse robotics market is to grow by more than US$4bn by 2026, as organisations increasingly demand efficiency in distribution channels. Research conducted by Technavio estimates the market size to grow by US$4.1bn, accelerating at a CAGR of 13.31% between 2021 and 2026. According to Statista, in 2020 the warehouse robotics market was worth some US$5.3bn worldwide, rising to US$6.2bn in 2021.
Read the full story: https://aimagazine.com/articles/warehouse-robotics-market-to-grow-by-over-4bn-by-2026
Drones replace warehouse workers to stop supply chain chaos
Supply chain robotics company Gather AI has landed a $10 million Series A financing round for its work with autonomous warehouse drones powered by artificial intelligence. Gather AI says an estimated US$150 billion is currently lost every year as a result of the problem of misplaced inventory, which they hope to solve with off-the-shelf drones paired with artificial intelligence software.
Read the full story: https://aimagazine.com/articles/warehouse-robotics-market-to-grow-by-over-4bn-by-2026
