1/ @MiniMax_AI M2.7 is live on SambaCloud — running at 435 output tokens/sec, more than 3x the next-fastest provider (per @ArtificialAnlys
). Built for the way coding agents actually work: Reading files Running tests Fixing errors Looping until the job is done
LLMS
-
MiniMax M2.7 Live: 435 Tokens/Sec for Coding Agents
By
–
-
SambaNova Responses API Accelerates High-Volume Agent Workflows
By
–
2/ Paired with SambaNova’s new Responses API, devs now get the fastest, most reliable foundation for high-volume agent workflows: • Large refactors
• Migrations
• Repo cleanup
• Multi-step coding tasks Because in agentic workflows, speed + cost determine whether an agent is -
LangSmith LLM Gateway Prevents AI Agent Overspending
By
–
Your agents can burn through $10k overnight before you notice. LangSmith LLM Gateway stops that. The platform where you already observe, evaluate, and deploy your agents now has a governance layer.
-
No filter beats filtered data in large LLM training
By
–
“A Bitter Lesson for Data Filtering” A common consensus is that LLMs need carefully filtered web data, because noisy data can easily hurts in small compute regimes. But this paper shows that with a large enough model size and training, the best filter is no filter. Raw Common
-
ChatGPT vs Gemini vs Claude vs Grok vs Perplexity
By
–
ChatGPT Vs Gemini Vs Claude Vs Grok Vs Perplexity
by @Khulood_Almani #GenerativeAI #ArtificialIntelligence #MI #MachineLearning -
Managed Deep Agents for Long-Horizon AI Tasks and Tool Use
By
–
Managed Deep Agents is built for agents that need to work over long time horizons, use tools, preserve context, and produce artifacts. A few examples of what teams are building: Support + triage agents Research agents Coding agents Data analysis agents Internal
-
Heima Hidden Llama speeds reasoning with abstract thinking tokens
By
–
AI could reason faster by thinking in abstract tokens instead of full sentences! Researchers from Zhejiang University, Adobe, and Northeastern University introduce Heima (Hidden Llama). It compresses lengthy Chain-of-Thought reasoning into a compact set of “thinking tokens,”
-
Open Source AI Agents Present a Significant Barrier to Entry Concern
By
–
The fact that the agents are open source is the scariest part, because the barrier to entry is zero.
-
AI Agent ‘Pancake’ Launches to Autonomously Run Companies
By
–
ACABAN DE LANZAR UN AGENTE DE IA QUE DIRIGE TU EMPRESA POR TI.
— Nico (@nicos_ai) 27 mai 2026
Y cada vez más empresas del futuro van a ser un "one-man business".
Se llama Pancake.
Una IA que aprende TODO sobre tu negocio y lo gestiona de forma autónoma.
Cómo funciona:
→ Crea un "cerebro" estructurado de… https://t.co/oSTwZD6t2j pic.twitter.com/oOSQspSRrvThey've just launched an AI agent that runs your company for you. And more and more companies of the future are going to be a "one-man business." It's called Pancake. An AI that learns EVERYTHING about your business and manages it autonomously. How it works:
→ Creates a -
LangChain Labs Announced for Continual Learning in Agents
By
–
ICYMI: We announced LangChain Labs at Interrupt. – An applied research effort focused on continual learning for agents – Early research partners: @NVIDIA
, @harvey
, @PrimeIntellect
, @Fireworks_AI
, @Baseten