Daniel @danielwarnur

@micro1_ai @cartesia LGI

micro1 x @cartesia: The Human Speech Data Project Every language, accent, and speaking style has its own rhythm, texture, and feeling. Building great voice AI means learning from the people who know those details best. That is why micro1 and Cartesia are launching The Human Speech Data Project, an initiative focused on improving the next generation of voice AI through high-quality speech data and human evaluation. The project brings together multilingual speakers, linguists, transcriptionists, native speakers, and voice actors to help: - Capture and evaluate natural conversational speech - Transcribe and annotate audio with a sharp ear for accuracy - Review AI-generated speech for naturalness, correctness, and edge cases - Bring expert judgment into the model improvement process Visit the link in the comments if you’d like to learn more about how you can contribute.

Two AI models can land the same pathology benchmark score for completely different reasons. Today we're introducing micro1's pathology-reasoning benchmark, the latest addition to our Realm Medical-Reasoning benchmark series. Built with practicing pathologists, it spans the range of cases a working service actually sees, from hematopathology and bone marrow workups to breast, thyroid, gastrointestinal, genitourinary, dermatopathology, and biomarker studies. Rather than testing medical knowledge in isolation, it measures something narrower and harder: whether a model can extract report facts exactly, preserve diagnostic limits, and avoid escalating to conclusions the specimen doesn't support. We scored three frontier models across the dataset: Claude Opus 4.8 - 82.6% GPT-5.5 - 76.3% Gemini 3.5 Flash - 75.7% However, the ranking was the least interesting part. The models were similarly strong at extracting facts and running calculations. Where they separated was judgment: knowing where the report ends. The most common way points were lost wasn't getting facts wrong. It was saying more than the report supports, resolving uncertainty the report left open, or naming a stage, biomarker, or treatment the specimen can't establish. We found that two models can land nearly the same score for completely opposite reasons. The aggregate numbers look close, but the trajectories tell a different story, and those differences get more interesting as the cases get harder. Our takeaway: what matters most isn't how often a model is right, but how it reasons when a report leaves room for doubt. Full report linked in the comments.

@micro1_ai great insight

Today we're excited to introduce the micro1·Crosby Contract Redlining Benchmark. In collaboration with @crosbylegal, we built a benchmark on real contract redlining to identify how frontier AI models perform at contract negotiation. Practicing attorneys negotiated multi-round SaaS agreements, and we tested how models handled the actual back-and-forth of a deal. Results: GPT-5.5: 50.5% Claude Fable 5: 47.3%* Gemini 3.5 Flash: 45.1% Claude Opus 4.8: 44.4% The biggest weakness showed up early in negotiations, meaning models performed much better once there was already context and prior redlines to react to, but struggled more when they had to make the first move. Our takeaway: today’s models are useful in legal workflows and can support live deals, but are not ready to negotiate one. Check out the full report at Crosby Intelligence.

John Sarihan @jsarihan

2 weeks ago

Contract negotiations are like poker games. The right answer depends on knowing your opponent, as much as knowing the law/rules. How good are frontier models at closing deals? With @micro1_ai we benchmarked frontier models on multiple contract negotiations, across several turns.

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@jsarihan incredible release & such a pleasure working with you all Crosby Intelligence 🔥

100%. there's many new job types emerging as a result of AI adoption throughout the economy - starting with training and evaluating models/agents. at micro1 we've created over 15,000 opportunities in the past few months alone. human involvement to train AI and to deliver the ultimate value that AI accelerates will always be there.

David Sacks @DavidSacks

2 weeks ago

Narrative violation.

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@DavidSacks entirely new job categories will continue to emerge as a result of AI adoption throughout the economy

the models are hungry for data... but everyone eats in the process 🫶💸

Ali Ansari @aliansarinik

2 weeks ago

Today, we’re committing $5,000,000 to launch the micro1 Company Data Partnerships Referral Program. For every company you refer, you can earn up to $25,000. Simply introduce a company, have them identify you as the referrer during onboarding, and once they enter into a paid data

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Earn up to $25k per successful company data partnership referral to micro1 Link in comments to get started

Ali Ansari @aliansarinik

2 weeks ago

Today, we’re committing $5,000,000 to launch the micro1 Company Data Partnerships Referral Program. For every company you refer, you can earn up to $25,000. Simply introduce a company, have them identify you as the referrer during onboarding, and once they enter into a paid data

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@aliansarinik 🤯🤯

Today, we’re committing $5,000,000 to launch the micro1 Company Data Partnerships Referral Program. For every company you refer, you can earn up to $25,000. Simply introduce a company, have them identify you as the referrer during onboarding, and once they enter into a paid data partnership with micro1, you’ll receive your referral payout. If you know a company that wants to turn its operational data into a recurring revenue stream while accelerating its adoption of AI through micro1's Data Partnership Program, we’d love an introduction. visit /data to get started x.com/APompliano/sta…

@APompliano @aliansarinik up to $25k per referral 👀

earn up to $25k per successful referral...

Anthony Pompliano 🌪 @APompliano

2 weeks ago

Most people don’t know you can get paid to help train AI models. Micro1 CEO @aliansarinik runs one of the leading companies paying people for their expertise. Now he is giving away $5 million to find companies with real world data. Worth paying attention to…

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Fable 5 is now live on micro1.ai/research and currently ranks #1 across all three of our expert reasoning benchmarks: tax, legal, and financial reasoning. These benchmarks evaluate how frontier models perform on domain-specific tasks that require expert knowledge, multi-step reasoning, and precise application of rules. Huge congrats to the @AnthropicAI team on an impressive release.

Claude @claudeai

3 weeks ago

Introducing Claude Fable 5: a Mythos-class model that we’ve made safe for general use. Its capabilities exceed those of any model we’ve ever made generally available.

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@aliansarinik insane opportunity

we’re partnering with 50 companies over the next two weeks, each with 50–200 employees, to help improve AI models using real-world company workflows. we believe the companies that helped build modern business workflows should participate in — and very much benefit from — the value created by the next generation of AI systems. for many companies, these partnerships can create a meaningful new revenue stream, often ranging from $100K to $2M+, with opportunities to become recurring over time. our goal is to do this in a way that is privacy-first, low-lift, and aligned with the work companies are already doing every day. if you’re interested in contributing to AI advancement while improving your own workflows alongside micro1 and our frontier AI lab partners, we’d love to hear from you. please reach out to to [email protected] if you’re an executive at a 50+ employee company, excited to potentially partner up!

a very large portion of our latest expansion & data pipeline requests have been coding. as model capabilities improve in a certain domain, data demand explodes even more. at micro1, we're building a world class coding research team. if you're interested in joining, check out micro1. ai/ research

5.5 million as of today

Ali Ansari @aliansarinik

8 months ago

now at 2M! 2,000,000 amazing experts have signed up on the micro1 platform to get matched with frontier AI opportunities, training the best LLMs.

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Introducing the Realm Financial Reasoning benchmark, our new evaluation of frontier AI on reasoning in finance and spreadsheet-grounded analysis. Tasks are built around the actual work product that practitioners deliver, from IFRS reconciliation workbooks and hedge-fund backtests to VC term sheet analyses and treasury cash-flow forecasts. Each task drops the model into a sandbox with the same source materials a human analyst would open: named-range Excel workbooks, broker PDFs, earnings call transcripts, monetary-policy decisions. Here's what the results showed (Pass@3): -GPT-5.5: 0.456 -Claude Opus 4.7: 0.398 -Gemini 3.1 Pro: 0.349 The three models score similarly, and none clears 50% on tasks that demand a judgment call. The back and middle office are defensible today, but on capital allocation questions current frontier models should be treated as research accelerators, not final decision-making support systems. Full report linked in the comments.