Happy Superbowl Sunday! Welcome to the weekend edition of InsideAI. I'm Rob May, CEO of Talla. I also host the AI at Work podcast. Our latest episode is with Bloomberg Beta investor James Cham. Our conversation actually sparked the commentary I'm writing about today - about economic incentives and AI adoption.
The most popular articles from our daily newsletter this week are below:
Summit, the world's most powerful supercomputer, broke a record for the fastest-running machine learning experiment. The experiment used algorithms to detect extreme weather patterns such as hurricanes out of a huge dataset of climate simulations. The project was run by the National Energy Research Scientific Computing Center at Lawrence Berkeley National Lab and is one of 19 projects chosen for the Summit Early Science Program, which grants access to the Summit supercomputer. — WIRED
The chip industry continues to move toward specialized chips for AI, according to both Microprocessor Report and Communications of the ACM. There is a flood of new custom ASICs (application-specific integrated circuits), including Amazon's Graviton chip and Huawei's Kunpeng 920 in response to the market dominance of Intel's Xeon processor for inference and Nvidia's GPU cloud-based training. John L. Hennessy and David A. Patterson, winners of the A.M. Turing award for their chip design work, say that the rise of domain-specific languages and architectures "will usher in a new golden age for computer architects." — ZDNET
TAE Technologies is collaborating with Google and using the Optometrist algorithm to find the ideal conditions for fusion. Fusion power is a theoretical concept of using nuclear fusion to generate electricity. The process requires fuel and extreme pressure and temperatures to create plasma in which fusion can happen. The Optometrist algorithm is being used to manage all the variables in the fusion testing being conducted at the Lawrence Livermore National Laboratory. — THE VERGE
The Verge asked AI experts to name their favorite books, stories, or blogs and compiled a list. The list includes "Profiles of the Future," by Arthur C. Clarke, "The Book of Why," by Judea Pearl and Dana Mackenzie, "Franchise" by Isaac Asimov, "The Diamond Age," by Neal Stephenson, "Machine Learning for Humans," by Vishal Maini and Samer Sabri, "Sorting Things Out," by Geoffrey C. Bowker and Susan Leigh Star, "The Master Algorithm," by Pedro Domingos. — THE VERGE
Researchers from MIT and Microsoft developed a model to improve autonomous systems. The model uses human input to help uncover "blind spots" in a system's training and to provide feedback. Humans can provide data by means of demonstration or correction. The researchers will present a pair of papers on the new model at the upcoming Association for the Advancement of Artificial Intelligence conference in Honolulu, Hawaii. — SCIENCE DAILY