4/ we conducted extensive safety evaluations before deployment, both before and after applying mitigations across frontier risk categories, behavioral alignment, and adversarial robustness. we found muse spark demonstrated strong refusal behavior across high-risk domains such as
AI
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Muse Spark: Meta’s Most Powerful Multimodal Reasoning Model
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2/ muse spark is a natively multimodal reasoning model w/ support for tool-use, visual chain of thought, & multi-agent orchestration. it's the most powerful model that meta has released. through its training process, we saw predictable scaling across pretraining, RL, & test-time
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MSL Releases Muse Spark, New AI Model Powering Meta AI
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1/ today we're releasing muse spark, the first model from MSL. nine months ago we rebuilt our ai stack from scratch. new infrastructure, new architecture, new data pipelines. muse spark is the result of that work, and now it powers meta ai.
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Shifting from IT-driven to OT-collaborative industrial solutions
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Traditional approach: seek buy-in for IT-conceived projects.
— Lucian Fogoros (@fogoros) 8 avril 2026
New approach: share ownership of OT-defined problems.
When OT teams become co-authors of solutions instead of defendants against them, the veto disappears.
Partner content with @InfluxDB. #influxdata_iiot #InfluxDB pic.twitter.com/4lBxkkxHY2Traditional approach: seek buy-in for IT-conceived projects.
New approach: share ownership of OT-defined problems.
When OT teams become co-authors of solutions instead of defendants against them, the veto disappears.
Partner content with @InfluxDB
. #influxdata_iiot #InfluxDB -
Meta Introduces Muse Spark, New Superintelligent Multimodal AI Model
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Excited to share what we've been building at Meta Superintelligence Labs! We just released Muse Spark, our first AI model. It's a natively multimodal reasoning model and the first step on our path to personal superintelligence. We've overhauled our entire stack to support scaling, and this is just the beginning. ai.meta.com/blog/introducing… [Translated from EN to English]
→ View original post on X — @scobleizer, 2026-04-08 16:00 UTC
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Deploy Multi-Agent Systems with A2A Protocol
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🔌 Deploy agents with A2A
— LangChain (@LangChain) 8 avril 2026
A2A is an agent-to-agent communication protocol, useful for building multi-agent systems. With LangSmith Deployments, you get A2A support out of the box!
Watch how: https://t.co/PF2FZbOb79
Docs: https://t.co/ETQ24g3KOX
A2A Protocol:… pic.twitter.com/TJVX5v9RZu🔌 Deploy agents with A2A A2A is an agent-to-agent communication protocol, useful for building multi-agent systems. With LangSmith Deployments, you get A2A support out of the box! Watch how: piped.video/SjGPXBNH614 Docs: docs.langchain.com/langsmith… A2A Protocol: a2a-protocol.org/latest/
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China Deploys Smart Robot to Keep Airports Bird-Free
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China Deploys Smart #Robot to Keep Airports Bird-Free 24/7
— Ronald van Loon (@Ronald_vanLoon) 8 avril 2026
by @PDChina#Robotics #Innovation #EmergingTech #TechForGood #Technology pic.twitter.com/PEPqJYeOhRChina Deploys Smart #Robot to Keep Airports Bird-Free 24/7 by @PDChina #Robotics #Innovation #EmergingTech #TechForGood #Technology
→ View original post on X — @ronald_vanloon, 2026-04-08 15:58 UTC
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Hedged Requests Reduce P99.99 DRAM Read Latency
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Hedged requests (apparently inspired by the Tail at Scale paper by myself and Luiz Barroso) applied within a single machine to replicating data across DRAM channels and issuing reads to all channels, using the one that comes back first. ~5-15X reduction in p99.99 read latency.
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Meta.ai platform now available for checkout
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Meta.ai is where you can check it out
→ View original post on X — @kimmonismus, 2026-04-08 15:53 UTC
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Anthropic Launches Mythos Model with Record SWE-Bench Performance
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I run growth at @AnthropicAI
. My job is to get our models into as many hands as possible. Mythos is by far the strongest model we've ever trained, and it's been a step-function change for us internally. It hit 93.9% SWE-bench Verified, found a ton of critical bugs including a