Robin Bordoli

President & CRO @Turingcom. Engineer turned GTM exec.. 4 AI & SaaS exits: Weights & Biases, Figure Eight, Marketo, Jive

[Robin Bordoli @rbordoli]

Very thoughtful analysis of distinction between human intelligence and LLM intelligence. Evokes @karpathy comparison of “building animals” vs “summoning ghosts”

[Valerio Capraro @ValerioCapraro]

Major preprint just out!

We compare how humans and LLMs form judgments across seven epistemological stages.

We highlight seven fault lines, points at which humans and LLMs fundamentally diverge:

The Grounding fault: Humans anchor judgment in perceptual, embodied, and social experience, whereas LLMs begin from text alone, reconstructing meaning indirectly from symbols.

The Parsing fault: Humans parse situations through integrated perceptual and conceptual processes; LLMs perform mechanical tokenization that yields a structurally convenient but semantically thin representation.

The Experience fault: Humans rely on episodic memory, intuitive physics and psychology, and learned concepts; LLMs rely solely on statistical associations encoded in embeddings.

The Motivation fault: Human judgment is guided by emotions, goals, values, and evolutionarily shaped motivations; LLMs have no intrinsic preferences, aims, or affective significance.

The Causality fault: Humans reason using causal models, counterfactuals, and principled evaluation; LLMs integrate textual context without constructing causal explanations, depending instead on surface correlations.

The Metacognitive fault: Humans monitor uncertainty, detect errors, and can suspend judgment; LLMs lack metacognition and must always produce an output, making hallucinations structurally unavoidable.

The Value fault: Human judgments reflect identity, morality, and real-world stakes; LLM "judgments" are probabilistic next-token predictions without intrinsic valuation or accountability.

Despite these fault lines, humans systematically over-believe LLM outputs, because fluent and confident language produce a credibility bias.

We argue that this creates a structural condition, Epistemia:
linguistic plausibility substitutes for epistemic evaluation, producing the feeling of knowing without actually knowing.

To address Epistemia, we propose three complementary strategies: epistemic evaluation, epistemic governance, and epistemic literacy.

Full paper in the first reply.

Joint with @Walter4C & @matjazperc

[Robin Bordoli @rbordoli]

We know change can be hard. @wandb is here to help customers who need to migrate off @neptune_ai

[Weights & Biases @wandb]

Huge congratulations to the Neptune team on their acquisition by OpenAI. It’s an incredible milestone and well-deserved.

For any customers affected by the shutdown of their services, wandb is ready to help ensure your experiments and workflows continue without interruption.

[Robin Bordoli @rbordoli]

If you’re an AI team deploying agents to production, you need RL to post train smaller, cheaper, more accurate models for your domain.

RL now available without the infra hassle. Christmas came early today.

[Weights & Biases @wandb]

RL X-mas came early. 🎄

For too long, building powerful AI agents with Reinforcement Learning has been blocked by GPU scarcity and complex infrastructure. That ends today.

Introducing Serverless RL from wandb, powered by @CoreWeave! We're making RL accessible to all.

[Weights & Biases @wandb]

We are teaming up with @OpenAI to show you, in just two free hours, how to ship production-ready AI agents!

Learn from @ilanbigio and @ash0ts as they break down tool chaining, memory, multi-agent patterns and evals.

Course drops on June 2nd! 👇

[Robin Bordoli @rbordoli]

Incisive WSJ article on how regulations have crippled Europe’s competitiveness in the global technology industry. As a Brit who left the UK 29 years ago to come to Silicon Valley, it saddens me to see my “mother” continent fall behind.

https://t.co/InRZ6IWstP

[Robin Bordoli @rbordoli]

If you’re trying to get AI agents working for your enterprise, don’t miss this event whether you’re an AI developer looking to iterate faster or an exec looking to get inspired.

[Weights & Biases @wandb]

🚀 Fully Connected 2025 • SF • June 17‑18

Day 1: hands‑on labs with safe LLMs, multi‑agent orchestration & deploy‑today fine‑tuning.

Day 2: AI Pioneer Series w/ @metaai, @GoogleAI, @Adobe, @CoreWeave, @windsurf_ai, @Pinterest, @Snowflake + more.

Get your ticket below!

[Robin Bordoli @rbordoli]

A new chapter begins…

[Weights & Biases @wandb]

Today we announced that we are being acquired by @CoreWeave, the AI Hyperscaler. 🪄🐝

We could not be prouder or more excited to join forces with this team.

Our CEO, @l2k, wrote a blog post with more details:
https://t.co/mTLuSlgAyQ

[Weights & Biases @wandb]

Curious how @cursor_ai became the go-to AI coding assistant, handling 100M+ requests daily and indexing billions of files in real time? 👀

Dive into the latest Gradient Dissent as @l2k sits down with Cursor co-founder @sualehasif996.

Vibe coders won’t want to miss this!

👇

[Weights & Biases @wandb]

Today we announced that we are being acquired by @CoreWeave, the AI Hyperscaler. 🪄🐝

We could not be prouder or more excited to join forces with this team.

Our CEO, @l2k, wrote a blog post with more details:
https://t.co/mTLuSlgAyQ

[Robin Bordoli @rbordoli]

Incredibly proud that @wandb enabled researchers at Berkeley to reproduce DeepSeek R1-Zero

They published the W&B workspace too

https://t.co/oJDnzpR2qi

[Jiayi Pan @jiayi_pirate]

We reproduced DeepSeek R1-Zero in the CountDown game, and it just works

Through RL, the 3B base LM develops self-verification and search abilities all on its own

You can experience the Ahah moment yourself for < $30
Code: https://t.co/UcGKN2SVGj

Here's what we learned 🧵

[Shawn Lewis @shawnup]

Our SWE-Bench submission has been accepted and is officially SOTA! Thanks SWE-Bench team for making such an important benchmark.

[Shawn Lewis @shawnup]

My o1-based AI programming agent is now state of the art on SWE-Bench Verified! It resolves 64.6% of issues.

This is the first fully o1-driven agent we know of. And we learned a ton building it.

[Robin Bordoli @rbordoli]

@jeremyphoward @jeremyphoward you should check out @shawnup's experience in building an o1 AI programming agent to form a more rounded POV on agents https://t.co/PVlAoaXmDB

[Shawn Lewis @shawnup]

My o1-based AI programming agent is now state of the art on SWE-Bench Verified! It resolves 64.6% of issues.

This is the first fully o1-driven agent we know of. And we learned a ton building it.

[Weights & Biases @wandb]

🪄 Think you’re an AI wizard? Prove it.

We’ve partnered w/ @AIExplainedYT to launch the Simple Bench Evals Competition—a challenge so tough, he said:

“If anyone gets 20/20 with a general-purpose prompt, I would be truly shocked.” 😳

Details below 👇

[Weights & Biases @wandb]

Excited to be in Jensen Huang’s CES keynote and expand our @nvidia collaboration!

Integrating @weave_wb into the AI Virtual Assistant Blueprint unlocks instant tracing and visibility.

More to come, as we dive into the future of agentic AI tools! 🚀

[Weights & Biases @wandb]

Our Co-founder and CEO, @l2k, has been named an AWS Gamechanger for pioneering generative AI progress!

Captured by legendary @langestudio, Lukas' portrait and the story of how we partnered with @AWScloud to empower @leonardoai to generate millions of images daily are featured at #AWSreInvent on a 16-foot video wall in Las Vegas this week.

[Weights & Biases @wandb]

📣 We're excited to announce that @weave_wb is now in GA! Join @l2k in this hands-on broadcast, to see how Weave is being used to build, evaluate and improve LLM applications in production with confidence! 👇 https://t.co/w09iy3ptz5

[Weights & Biases @wandb]

🔥 We've been cooking!

Tune in LIVE tomorrow 9am PT, to hear @l2k unveil exciting news for AI developers straight from the cracked team at @weave_wb!

YT link 👇

[Weights & Biases @wandb]

We just dropped the latest episode of #GradientDissent with @juliangreensf and @l2k discussing AI’s role in weather forecasting.

They dive into:
📊 The shift from physics-based to AI-driven weather  models
🌍 Democratizing forecasting for better climate solutions
🌪️ How AI predicts extreme weather events

[Weights & Biases @wandb]

🚀 Exciting News!

@wandb and @MicrosoftAzure join forces to streamline fine-tuning models like GPT-4 &amp; GPT-4o on Azure OpenAI Service!

Got a WANDB_API_KEY &amp; using Azure? Now you can keep an eye on the loss curves of your GPT-4o finetune dropping 👀

More details 👇