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Nvidia’s new AI model, Llama-3.1-Nemotron-70B-Instruct, is outperforming GPT-4o with impressive benchmark results. It quietly launched on Hugging Face, surpassing OpenAI’s and Anthropic’s models in multiple key performance tests. The model’s strong scores and focus on user alignment make it a game-changer in the AI landscape. 🔍 *Key Topics Covered:*– Nvidia’s Llama-3.1-Nemotron-70B-Instruct outperforms GPT-4o, surpassing industry benchmarks– The model’s revolutionary alignment capabilities and how it addresses user needs more effectively– Nvidia’s strategic move into AI software, challenging traditional leaders in the AI field 🎥 *Wha...... Read Full article on HadNews

The walking, talking, dancing Optimus robots at the recent Tesla demonstration generated huge excitement. But this turned to disappointment as it became apparent that much of what was happening was actually being controlled remotely by humans. As much as this might still be a fascinating glimpse of the future, it’s not the first time that robots have turned out to be a little too good to be true. Take Sophia, for instance, the robot created by Texas-based Hanson Robotics back in 2016. She was presented by the company as essentially an intelligent being, prompting numerous tech specialists to call this out as well beyond our capabilities a...... Read Full article on HadNews

This is a guest post. The views expressed here are solely those of the authors and do not represent positions of IEEE Spectrum, The Institute, or IEEE.Many in the civilian artificial intelligence community don’t seem to realize that today’s AI innovations could have serious consequences for international peace and security. Yet AI practitioners—whether researchers, engineers, product developers, or industry managers—can play critical roles in mitigating risks through the decisions they make throughout the life cycle of AI technologies.There are a host of ways by which civilian advances of AI could threaten peace and security. Some are direc...... Read Full article on HadNews

This article is part of our exclusive IEEE Journal Watch series in partnership with IEEE Xplore.Programmers have spent decades writing code for AI models, and now, in a full circle moment, AI is being used to write code. But how does an AI code generator compare to a human programmer?A study published in the June issue of IEEE Transactions on Software Engineering evaluated the code produced by OpenAI’s ChatGPT in terms of functionality, complexity and security. The results show that ChatGPT has an extremely broad range of success when it comes to producing functional code—with a success rate ranging from anywhere as poor as 0.66 percent and...... Read Full article on HadNews

Anthropic, a company that does research into AI safety, is calling for proposals on ways to evaluate advanced learning models. The rapid growth of AI means there are new AI providers and models all the time. Every major tech company has its own model, while there are dozens more smaller ones as well. That means that the industry has a rising benchmarking problem, making it tough to accurately evaluate how well an AI model performs. Not only is it hard to state how effective a model is, but it’s also hard to evaluate the risks involved with AI safety. Anthropic is calling for proposals to plug this gap in AI evaluation. “Developing high...... Read Full article on HadNews

You might have heard that artificial intelligence is going to revolutionize everything, save the world and give everyone superhuman powers. Alternatively, you might have heard that it will take your job, make you lazy and stupid, and make the world a cyberpunk dystopia. Consider another way to look at AI: as an assistive technology – something that helps you function. With that view, also consider a community of experts in giving and receiving assistance: the disability community. Many disabled people use technology extensively, both dedicated assistive technologies such as wheelchairs and general-use technologies such as smart home devices...... Read Full article on HadNews