Yeah the learning mechanism is what separates this from static tool libraries
AI
-
Manual Debugging Doesn’t Scale in Modern Development
By
–
Exactly, the manual debugging doesn't scale
-
SASInnovate Conference: 200+ Sessions on Data and AI Skills
By
–
Don't miss out on the incredible opportunity to join #SASInnovate! Experience 3+ days of invaluable networking, choose from 200+ breakout sessions + learn from expert speakers who will elevate your data and AI skills. Reserve your seat http://
2.sas.com/6013B6dGOf -
Self-Evolving Agents: The Future of AI Technology
By
–
Rightly said, I think self-evolving agents are the future.
-
Inference Engine Batch Size and GPU Chat Announcement
By
–
this seems big. tho curious how this ties into inventory mgmt, fulfillment, etc. using fb marketplace infra or…
-
RetinaNet and Focal Loss: Solving Class Imbalance in Object Detection
By
–
🎯 RetinaNet & Focal Loss: Fixing Class Imbalance in Object Detection
— Satya Mallick (@LearnOpenCV) 25 mars 2026
Single stage detectors were fast but struggled with class imbalance. In 2017, researchers at Facebook AI introduced RetinaNet with a new loss function Focal Loss.
By down-weighting easy background examples… pic.twitter.com/1gQ9p8Ku7jRetinaNet & Focal Loss: Fixing Class Imbalance in Object Detection Single stage detectors were fast but struggled with class imbalance. In 2017, researchers at Facebook AI introduced RetinaNet with a new loss function Focal Loss. By down-weighting easy background examples
-
Snorkel AI Hiring ML Training Infrastructure Engineer for RL Scaling
By
–
Scaling RL training for agentic models is one of the hardest infra problems in ML right now and honestly, one of the most exciting jobs🔥 Our research team @SnorkelAI is deep in RLFT (data valuation, curriculum learning, and more). We're #hiring an ML Training Infra engineer who's actually done this at scale with complex environments and medium sized models. If that sounds like you (or someone you know), DM me or drop a comment 👇 #MLJobs | Link in thread
→ View original post on X — @snorkelai, 2026-03-25 14:25 UTC
-
Meta’s $700B AI Investment Fails to Produce Competitive Models
By
–
I did a calculation. Meta invested ~700b in AI overall. ScaleAI acqui-hire ~$14.3
Manus accquisition ~$2-3b
several ~100m for hirings. They have invested over $600b in data center. And for some reason they still dont have any upcoming model that could compete with even chinese -
Block Diffusion Language Models Enable Faster AI Reasoning
By
–
What if your AI could reason smarter AND faster, especially on complex tasks? A collaboration from Fudan University, Peking University, and Meituan LongCat Team just made it happen! They've developed a new framework for Block Diffusion Language Models (BDLMs) that lets the AI