totally got harder for open-source maintainers but I suspect that it got even harder for closed-source maintainers to stay safe (even if they don't necessary realize it yet because they've been breached silently)
AI
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Gut Microbiome Signature Predicts Parkinson’s Disease Risk
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We've known the gut-brain axis is a key underpinning of Parkinson's disease. Today, for the 1st time, a gut microbiome signature denoting risk found in healthy individuals with genetic predisposition @NatureMedicine https://
nature.com/articles/s4159
1-026-04318-5
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Simple Prompting Trick Improves LLM Randomness and Output Diversity
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Getting LLMs to simulate “true” randomness or generate diverse outputs is surprisingly difficult. We found a simple prompting trick that solves this by having the model generate and manipulate a random string. To be presented at #ICLR2026 this week!
— hardmaru (@hardmaru) 20 avril 2026
Blog: https://t.co/CyevqqJ5ej https://t.co/dN0yZZ5MijGetting LLMs to simulate “true” randomness or generate diverse outputs is surprisingly difficult. We found a simple prompting trick that solves this by having the model generate and manipulate a random string. To be presented at #ICLR2026 this week! Blog: https://
pub.sakana.ai/ssot -
@testingcatalog — 2026-04-20
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Moonshot AI is rolling out Kimi K2.6 on Kimi Chat and APIs. All models got upgraded. – Kimi K2.6 Instant
– Kimi K2.6 Thinking – Kimi K2.6 Agent – Kimi K2.6 Agent Swarm Did you get it already? -
Can LLMs Generate Truly Random Outputs Faithfully
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Can LLMs flip coins in their heads?
— Sakana AI (@SakanaAILabs) 20 avril 2026
When prompted to “Flip a fair coin” 100 times, the heads to tails ratio drifts far from 50:50. LLMs can understand what the target probability should be, but generating outputs that faithfully follow a given distribution is a separate problem.… pic.twitter.com/XyF7Xnj8LlCan LLMs flip coins in their heads? When prompted to “Flip a fair coin” 100 times, the heads to tails ratio drifts far from 50:50. LLMs can understand what the target probability should be, but generating outputs that faithfully follow a given distribution is a separate problem.
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AI-Powered Robot Bicycle Mimics Human Athletic Performance
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#AI-Powered Robot Bicycle Mimics Human Athletic Performance
— Ronald van Loon (@Ronald_vanLoon) 20 avril 2026
via @ZappyZappy7
#Robotics #ArtificialIntelligence #Innovation #Technology pic.twitter.com/eEAv1PQHYW#AI-Powered Robot Bicycle Mimics Human Athletic Performance
via @ZappyZappy7 #Robotics #ArtificialIntelligence #Innovation #Technology -
Developers leverage 262K context window limits in AI workflows
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Devs are taking full advantage of the 262K limit, absolutely stuffing the context window without worrying about the bill Test it in your own workflows right now:
→ https://
openrouter.ai/openrouter/ele
phant-alpha
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Top Autonomous AI Agents Processing Billions Tokens Daily
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Top autonomous agents are already feasting on it! → @OpenClaw has pushed 107 Billion tokens
→ @Kilocode and @Claudeai routed 54 Billion combined
→ The Hermes Agent is nearing 26 Billion tokens It maintains 100% provider uptime. It is fast… and it won't cost you a dime. -
Elephant Alpha Achieves Perfect Score in AI Reliability Tests
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Elephant Alpha is built for raw reliability. In AI BENCHY's "Anti-AI Tricks" tests, it hit a perfect 10.0 for consistency, completely ignoring the flaky behavior of other open models. It also skips the reasoning token trap: You get direct answers with zero reasoning bloat,
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Mystery Provider Launches Free 100B Parameter Model Elephant Alpha
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This is fascinating. A mystery stealth provider just flipped the entire market upside down. They dropped a massive 100B parameter model on @OpenRouter called Elephant Alpha. Best part? It's absolutely FREE Here's the tech stack you get: → 100B parameter intelligence.
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