Artificial Intelligence (AI)
New training approach could help AI agents perform better in uncertain conditions
A home robot trained to perform household tasks in a factory may fail to effectively scrub the sink or take out the trash when deployed in a user’s kitchen, since this new environment differs from its training space. To avoid this, engineers often try to match the simulated training environment as closely as possible with…
NVIDIA AI Researchers Introduce FFN Fusion: A Novel Optimization Technique that Demonstrates How Sequential Computation in Large Language Models LLMs can be Effectively Parallelized
Large language models (LLMs) have become vital across domains, enabling high-performance applications such as natural language generation, scientific research, and conversational agents. Underneath these advancements lies the transformer architecture, where alternating layers of attention mechanisms and feed-forward networks (FFNs) sequentially process tokenized input. However, with an increase in size and complexity, the computational burden required…
Why Time is QA Tester’s Superpower and Pressure its Kryptonite! – Spritle software
Introduction In the breakneck world of software development, where new apps and features are demanded yesterday, Quality Assurance (QA) teams often find themselves under immense pressure. They’re expected to give the thumbs-up on complex software, often against a relentlessly ticking clock. But here’s the truth: squeezing QA like a lemon doesn’t magically produce better software—it…
How Well Can LLMs Actually Reason Through Messy Problems?
The introduction and evolution of generative AI have been so sudden and intense that it’s actually quite difficult to fully appreciate just how much this technology has changed our lives. Zoom out to just three years ago. Yes, AI was becoming more pervasive, at least in theory. More people knew some of the things it…
Evaluating social and ethical risks from generative AI
Introducing a context-based framework for comprehensively evaluating the social and ethical risks of AI systems Generative AI systems are already being used to write books, create graphic designs, assist medical practitioners, and are becoming increasingly capable. Ensuring these systems are developed and deployed responsibly requires carefully evaluating the potential ethical and social risks they may…
Making higher education more accessible to students in Pakistan
Taking out a loan to attend college is an investment in your future. But unlike in the United States, students in Pakistan don’t have easy access to college loans. Instead, most families must stomach higher interest rates for personal loans that can require collateral like land or homes. As a result, college is inaccessible for…
Scaling Up Reinforcement Learning for Traffic Smoothing: A 100-AV Highway Deployment
Training Diffusion Models with Reinforcement Learning We deployed 100 reinforcement learning (RL)-controlled cars into rush-hour highway traffic to smooth congestion and reduce fuel consumption for everyone. Our goal is to tackle “stop-and-go” waves, those frustrating slowdowns and speedups that usually have no clear cause but lead to congestion and significant energy waste. To train efficient…
Prof. Ami Moyal, President of Afeka College of Engineering – Interview Series
Prof. Ami Moyal is the President of Afeka College of Engineering and the newly elected Chairman of the Israeli Council for Higher Education’s Planning & Budgeting Committee. He holds a Ph.D. in Electrical & Computer Engineering from Ben-Gurion University and is an expert in automatic speech recognition. Before becoming Afeka’s President in 2014, he founded…
A glimpse of the next generation of AlphaFold
Research Published 31 October 2023 Authors Google DeepMind AlphaFold team and Isomorphic Labs team Progress update: Our latest AlphaFold model shows significantly improved accuracy and expands coverage beyond proteins to other biological molecules, including ligands Since its release in 2020, AlphaFold has revolutionized how proteins and their interactions are understood. Google DeepMind and Isomorphic Labs…
At the core of problem-solving
As director of the MIT BioMicro Center (BMC), Stuart Levine ’97 wholeheartedly embraces the variety of challenges he tackles each day. One of over 50 core facilities providing shared resources across the Institute, the BMC supplies integrated high-throughput genomics, single-cell and spatial transcriptomic analysis, bioinformatics support, and data management to researchers across MIT. The BioMicro…