May 2023 Archive
10771.
Mystery of Vital Cell Protein Solved After 30 Years (1998) (www2.lbl.gov)
10772.
Gave GPT-4 access to use Chrome interactively on my desktop (github.com)
10773.
Why Are Indian Startups Imploding? (bloomberg.com)
10774.
Mojo Programming Manual (docs.modular.com)
10775.
The FSF's Board Candidates (fsf.org)
10776.
New Relic unveils Grok – OpenAI code fixes based on telemetry data (newrelic.com)
10777.
Cozo DB 0.7 is released (docs.cozodb.org)
10778.
New: HP 15C Collectors Edition (hpmuseum.org)
10779.
Identifying Toxic Consumer Products: A Novel Data Set Reveals Air Emissions (pubs.acs.org)
10780.
Xerox Donates Legendary PARC Research Center (spectrum.ieee.org)
10781.
10782.
How to explain cardinals vs. ordinals to a six-year-old (blog.rongarret.info)
10783.
Webb telescope detects mysterious water vapor in a nearby star system (cnn.com)
10784.
A cavern beneath a West Antarctic glacier is teeming with life (sciencenews.org)
10785.
The Glorious Return of a Humble Car Feature (slate.com)
10786.
Why Mojo? (Modular’s new Python compatible language for AI) (docs.modular.com)
10787.
Mechanically reconfigurable van der Waals devices via low-friction gold sliding (science.org)
10788.
OBS Studio 29.1 Adds Support for AV1 Encoding (blogs.nvidia.com)
10789.
A Very Big Small Leap Forward in Graph Theory (quantamagazine.org)
10790.
GPT AI Enables Scientists to Passively Decode Thoughts (artisana.ai)
10791.
What Is the Fluidic Telescope? (nasa.gov)
10792.
Wicked Bible (en.wikipedia.org)
10793.
Die photo of the Intel iAPX 432 processor (oldbytes.space)
10794.
ByteDance’s ‘Sensitive Words’ Tool Monitors Discussion of China, Trump, Uyghurs (forbes.com)
10795.
Tech Predictions for 2023 and Beyond (allthingsdistributed.com)
10796.
Thought Leadership for Technical Founders (heavybit.com)
10797.
ChatGPT Plugin Pioneers Event: Igniting the AI Revolution (community.openai.com)
10798.
SQLite: Professional Support and Extension Products (sqlite.org)
10799.
Colorado kills law that made it harder for cities to offer Internet service (arstechnica.com)
10800.
Dissecting Recall of Factual Associations in Auto-Regressive Language Models (arxiv.org)