The latest AI News. Learn about LLMs, Gen AI and get ready for the rollout of AGI. Wes Roth covers the latest happenings in the world of OpenAI, Google, Anthropic, NVIDIA and Open Source AI.
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00:00 singularity is near.
01:37 Sam Altman’s Blog Post \
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OpenAI CEO Sam Altman said the first artificial intelligence agents might enter the workforce this year as his company inches closer to developing humanlike artificial general intelligence (AGI).
“We believe that, in 2025, we may see the first AI agents ‘join the workforce’ and materially change the output of companies,” said Altman in a blog post titled “Reflections” on Jan. 6.
AI agents or agentic AI refers to artificial intelligence systems that exhibit autonomous decision-making and goal-directed behavior. They can autonomously understand complex goals, make decisions, take actions with minimal human intervention and execute multi-step reasoning processes.
Machine learning algorithms significantly impact decision-making in high-stakes domains, necessitating a balance between fairness and accuracy. This study introduces an in-processing, multi-objective framework that leverages the Reject Option Classification (ROC) algorithm to simultaneously optimize fairness and accuracy while safeguarding protected attributes such as age and gender.
Quantum computing stocks are soaring, but do the rising stock prices make sense?
Over the last couple of years, technology stocks have captivated the investment world thanks in large part to breakthroughs in artificial intelligence (AI).
Within the AI realm, semiconductor stocks in particular have benefited greatly. This is due to the fact that semiconductor companies such as Nvidia, Advanced Micro Devices, and Broadcom make important infrastructure such as graphics processing units (GPUs) and network equipment that are used in data centers, and without them, generative AI would be more of a lofty idea than a reality.
A recent award from the U.S. Defense Advanced Research Projects Agency (DARPA) brings together researchers from Massachusetts Institute of Technology (MIT), Carnegie Mellon University (CMU), and Lehigh University (Lehigh) under the Multiobjective Engineering and Testing of Alloy Structures (METALS) program. The team will research novel design tools for the simultaneous optimization of shape and compositional gradients in multi-material structures that complement new high-throughput materials testing techniques, with particular attention paid to the bladed disk (blisk) geometry commonly found in turbomachinery (including jet and rocket engines) as an exemplary challenge problem.
A DARPA-funded collaborative multi-university team pursues new AI-enhanced design tools and high-throughput testing methods for next-generation turbomachinery.