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Import AI 456: RSI and economic growth; radical optionality for AI regulation; and a neural computer
What laws does superintelligence demand?
Meta buys robotics startup to bolster its humanoid AI ambitions
Meta bought humanoid startup Assured Robot Intelligence to beef up its AI models for robots, the company said.
AWS Generative AI Model Agility Solution: A comprehensive guide to migrating LLMs for generative AI production
In this post, we introduce a systematic framework for LLM migration or upgrade in generative AI production, encompassing essential tools, methodologies, and best practices. The framework facilitates transitions between different LLMs by providing robust protocols for prompt conversion and optimization.
Meta says its business AI now facilitates 10 million conversations a week
Meta said over 8 billion advertisers have used at least one of its gen AI tools
Get to your first working agent in minutes: Announcing new features in Amazon Bedrock AgentCore
Today, we're introducing new capabilities that further streamline the agent building experience, removing the infrastructure barriers that slow teams down at every stage of agent development from the first prototype through production deployment.
World models
AI systems have already gained impressive mastery over the digital world, but the physical world is still humanity’s domain. As it turns out, building an AI system that can compose a novel or code an app is far easier than developing one that can fold laundry or navigate a city street. To get there, many…
Resistance
Turns out not everyone wants to live in the future that AI companies are building. People from all walks of life are speaking out against rising electricity bills from data centers, disappearing jobs, chatbots’ impact on teen mental health, the military’s use of AI, and copyright infringement—among other concerns. This anti-AI movement is taking shape…
China’s open-source bet
Silicon Valley AI companies follow a familiar playbook: Keep the secret sauce behind an API, and charge for every drop. China’s leading AI labs are playing a different game: They ship models as downloadable “open-weight” packages. This lets developers adapt the models and run them on their own hardware to build products without negotiating a…
Modernizing the Facebook Groups Search to Unlock the Power of Community Knowledge
We’ve fundamentally transformed Facebook Groups Search to help people more reliably discover, sort through, and validate community content that’s most relevant to them. We’ve adopted a new hybrid retrieval architecture and implemented automated model-based evaluation to address the major friction points people experience when searching community content. Under this new framework, we’ve made tangible improvements [...] Read More... The post Modernizing the Facebook Groups Search to Unlock the Power of Community Knowledge appeared first on Engineering at Meta .
The New Unicorn Count Reached A 4-Year High In March, Led By Robotics, Frontier Labs And AI Infrastructure
A total of 37 companies joined The Crunchbase Unicorn Board in March, the highest monthly count in close to four years, Crunchbase data shows. The robotics sector led unicorn creation last month, with six new billion-dollar startups.
Import AI 454: Automating alignment research; safety study of a Chinese model; HiFloat4
At what point do the financial markets price in the singularity?
Capacity Efficiency at Meta: How Unified AI Agents Optimize Performance at Hyperscale
We’re sharing insights into Meta’s Capacity Efficiency Program, where we’ve built an AI agent platform that helps automate finding and fixing performance issues throughout our infrastructure. By leveraging encoded domain expertise across a unified, standardized tool interface these agents help save power and free up engineers’ time away from addressing performance issues to innovating on [...] Read More... The post Capacity Efficiency at Meta: How Unified AI Agents Optimize Performance at Hyperscale appeared first on Engineering at Meta .
Use-case based deployments on SageMaker JumpStart
We're excited to announce the launch of Amazon SageMaker JumpStart optimized deployments. SageMaker JumpStart improved deployments address the need for rich and straightforward deployment customization on SageMaker JumpStart by offering pre-defined deployment configurations, designed for specific use cases. Customers maintain the same level of visibility into the details of their proposed deployments, but now deployments are optimized for their specific use case and performance constraint.
[AINews] Top Local Models List - April 2026
a quiet day lets us check in on the local models scene
Meta AI app climbs to No. 5 on the App Store after Muse Spark launch
The app was ranking No. 57 on the App Store just before Meta AI's new model launched. Now it's No. 5 — and rising.
[AINews] Meta Superintelligence Labs announces Muse Spark, first frontier model on their completely new stack
a quiet day lets us reflect on MSL finally shipping!
Accelerate agentic tool calling with serverless model customization in Amazon SageMaker AI
In this post, we walk through how we fine-tuned Qwen 2.5 7B Instruct for tool calling using RLVR. We cover dataset preparation across three distinct agent behaviors, reward function design with tiered scoring, training configuration and results interpretation, evaluation on held-out data with unseen tools, and deployment.
How Meta Used AI to Map Tribal Knowledge in Large-Scale Data Pipelines
AI coding assistants are powerful but only as good as their understanding of your codebase. When we pointed AI agents at one of Meta’s large-scale data processing pipelines – spanning four repositories, three languages, and over 4,100 files – we quickly found that they weren’t making useful edits quickly enough. We fixed this by building [...] Read More... The post How Meta Used AI to Map Tribal Knowledge in Large-Scale Data Pipelines appeared first on Engineering at Meta .
AI companies are building huge natural gas plants to power data centers. What could go wrong?
Meta, Microsoft, and Google are all betting big on new natural gas power plants to run their AI data centers. They may regret it.
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