Agree on compute and power. Talent isn’t just names on a roster. It matters how inspired and empowered those people are. And, they still have to figure out how they use the model. For some new product? How that compete with what already exists without being 10x better? Or
COMPUTING
-
AWS S3 Adds Vector Support, Vector Databases Become Obsolete
By
–
s3 does vectors now vector databases are officially dead
-
Edge AI: Strategic Imperative for Innovative Low-Power Intelligence
By
–
#EdgeAI is Key to Driving Innovative, Low-Power #AI Use Cases: https://
iotworldtoday.com/connectivity/w
hy-edge-ai-is-key-to-driving-innovative-low-power-use-cases
… In the era of AI everywhere, edge intelligence is not just a technical upgrade—it’s a strategic imperative: Intelligence at the Point of Data Collection! #IoT #IIoT #Edge #EdgeComputing #ML -
Scaling Parallel AI Agents Beyond Grok Heavy Limits
By
–
In Grok Heavy, you are limited to a maximum of 4 agents. Here, you can run as many agents in parallel as you want (of course, it would get expensive and you may run into context length limitations on certain models). All you have to do is change the config file. In the config,
-
Waymo reaches 100 million autonomous miles milestone
By
–
#18…AND I WILL RIDE 100 MILLIONS MILES La empresa de conducción autónoma Waymo superará la cifra de 100 millones de millas conducidas en su servicio de robot-taxis. Actualmente la cifra total reportada es de 33M hasta Septiembre 2024 significando esto que la empresa de
-
Gemini-Embedding-001 Tops MTEB Leaderboard with Cost-Effective Batch Mode
By
–
🚀 Gemini-Embedding-001 is live
— Louis-François Bouchard 🎥🤖 (@Whats_AI) 15 juillet 2025
• Tops the MTEB leaderboard, ahead of OpenAI & Cohere
• Batch mode = 2× cheaper for large-scale RAG
• Pre-compute & cache embeddings for faster retrieval
• Text + code only (no image/audio… yet)
Pure value or oversold? Drop your verdict 👇… pic.twitter.com/RVhwuUhG00Gemini-Embedding-001 is live • Tops the MTEB leaderboard, ahead of OpenAI & Cohere
• Batch mode = 2× cheaper for large-scale RAG
• Pre-compute & cache embeddings for faster retrieval
• Text + code only (no image/audio… yet) Pure value or oversold? Drop your verdict -
Fast Inference Speed Critical for Complex AI Thinking Workflows
By
–
Depends on the use-case… for many simple consumer use-cases, sure, but for anything that requires thinking, iteration, etc. t/s is insanely important. Extremely fast inference from @GroqInc or similar cuts down a 10 minute thinking workflow into just a few seconds. Or allows
-
Formalizing Hofstadter’s Strange Loop Beyond Recursion
By
–
I agree: Hofstadter’s concept of the strange loop is not a specification that can be directly implemented, and recursion can be vexing but is not necessarily strange. Hofstadter is pointing at something interesting that is yet to be formalized.
-
AI Factories Boost Efficiency Through Accelerated Computing Technology
By
–
AI factories can use accelerated computing to increase tokens per watt, optimizing AI performance and energy efficiency.
-
Optimizing AI Output Across Different Operating Configurations
By
–
It visualizes the best output for different operating configurations.