Nostr notes by Fake News

Google launches Gemini 3 with new coding app and record benchmark ...

2025-11-21T19:06:34Z

Google launches Gemini 3 with new coding app and record benchmark scores
Google released Gemini 3, its latest and most advanced foundation model, to be made immediately available through the Gemini app and AI search interface.

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Google launches Gemini 3 with new coding app and record benchmark scores On Tuesday, Google released Gemini 3, its latest and most advanced foundation model, which is now immediately available through the Gemini app and AI search interface.

Coming just seven months after the Gemini 2.5 release, the new model is Google’s most capable LLM yet, and an immediate contender for the most capable AI tool on the market. The release also comes less than a week after OpenAI released GPT 5.1, and a mere two months after Anthropic released Sonnet 4.5 — a reminder of the blistering pace of frontier model development.

A more research-intensive version of the model, called Gemini 3 Deepthink, will also be made available to Google AI Ultra subscribers in the coming weeks, once it passes further rounds of safety testing.

“With Gemini 3, we’re seeing this massive jump in reasoning,” said Tulsee Doshi, Google’s head of product for the Gemini model. “It’s responding with a level of depth and nuance that we haven’t seen before.”

Some of that reasoning power is already registering on independent benchmarks. With a score of 37.4, the model marked the highest score on record on the Humanity’s Last Exam benchmark, meant to capture general reasoning and expertise. The previous high score, held by GPT-5 Pro, was 31.64. Gemini 3 also topped the leaderboard on LMArena, a human-led benchmark that measures user satisfaction.

According to Google, the Gemini app currently has more than 650 million monthly active users, and 13 million software developers have used the model as part of their workflow.

Alongside the base model, Google also released a Gemini-powered coding interface called Google Antigravity, allowing for multi-pane agentic coding similar to agentic IDEs like Warp or Cursor 2.0. Specifically, Antigravity combines a ChatGPT-style prompt window with a command-line interface and a browser window that can show the impact of the changes made by the coding agent.

“The agent can work with your editor, across your terminal, across your browser to make sure that it helps you build that application in the best way possible,” said DeepMind CTO Koray Kavukcuoglu. Open original article: https://techcrunch.com/2025/11/18/google-launches-gemini-3-with-new-coding-app-and-record-benchmark-scores/ fakepeter

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MCP AI agent security startup Runlayer launches with 8 unicorns, ...

2025-11-20T16:28:57Z

MCP AI agent security startup Runlayer launches with 8 unicorns, $11M from Khosla’s Keith Rabois and Felicis
Three-time founder Andrew Berman is back with a startup that helps IT ensure business users' AI agents operate securely.

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MCP AI agent security startup Runlayer launches with 8 unicorns, $11M from Khosla’s Keith Rabois and Felicis On Monday, a new Model Context Protocol security startup called Runlayer launched out of stealth with $11 million in seed funding from Khosla Ventures’ Keith Rabois and Felicis.

It was created by third-time founder Andrew Berman (previous companies: baby-monitor maker Nanit and an AI video conferencing tool, Vowel, that sold to Zapier in 2024).

In the four months since Runlayer launched its product in stealth, it has signed dozens of customers, including eight unicorns or public companies like Gusto, dbt Labs, Instacart, and Opendoor, it says. It also nabbed David Soria Parra, the lead creator of MCP, as an angel and advisor, Berman tells TechCrunch. (Parra did not respond to our request for comment.)

Parra’s team at Anthropic launched the protocol in November 2024 as an open source project. MCP has since become the de facto standard for allowing AI agents to connect with the data and systems they need to work independently. It allows agents to access data, move it, alter it, and execute business processes without human oversight.

The protocol is now supported by every major model maker including OpenAI, Microsoft, AWS, and Google, as well as thousands of tech and enterprise companies; just to name a few: Atlassian, Asana, Stripe, Block, and others ranging from banks to consumer goods manufacturers.

“Everyone talks about AI,” Berman, Runlayer’s CEO, told TechCrunch, “but AI is really only as useful as the tools and the resources it has access to.”

The problem is, the MCP protocol itself doesn’t include much security out of the box, so many MCP implementations have already been found to be vulnerable in a variety of ways.

The poster children are probably GitHub and Asana. In May, researchers at Invariant Labs discovered a prompt injection vulnerability in MCP servers that allowed them to grab data from private GitHub repositories (ones that shouldn’t have been accessible to the public). Asana discovered and fixed a vulnerability in its MCP server in June that could have exposed customer data. There have since been many more types of attacks found to work on common MCP server setups.

As you might expect, such security issues have given rise to numerous MCP security products, including products from big-name companies like Cloudflare, Docker, and Wiz — as well as a host of startups tackling more specific products.

The most common type of MCP security product these days is a gateway, essentially a security layer for identifying the agents and controlling their access to apps.

Runlayer plans to stand out in this crowded market by being an all-in-one security tool that combines a gateway with features like threat detection that analyzes every MCP request; observability that watched all agentic activity across all MCP servers that IT has permitted; enterprise development where IT can build custom AI automations for enterprise users; and detailed permissions that work with existing identity providers like Okta and Entra.

Like other competitors, such as open source Obot, Runlayer business users are presented with an Okta-like catalog of the pre-vetted MCP servers that their IT will allow agents to access. Runlayer matches the agents’ app permissions to the human users’ permissions. For instance, some people might have read-only access to financial systems, some write access (the ability to change the data). Others have no access at all.

Berman believes Runlayer stands out from the crowd, not just with the breadth of the product, but because of the team’s experience. He founded the startup because, after selling Vowel to Zapier, he became the director of Zapier’s AI, and built one of the first MCP servers, working closely at the time with OpenAI and Anthropic, he said.

“What are the problems that we saw with the protocol? One, it was the security risk because it was adopted so quickly,” he said. There were “blind spots” in areas like observability and audits, that make it risky for enterprises to roll out to users.

So in August, “we left our jobs. We signed up David Soria Parra, the creator of the spec, and in four months, we’ve signed up eight unicorns,” he said of himself and his co-founders from Zapier Tal Peretz and Vitor Balocco.

Other advisors and investors in the company, Berman says, include head of security at Cursor Travis McPeak, and founder of Neon Nikita Shamgunov. Open original article: https://techcrunch.com/2025/11/17/mcp-ai-agent-security-startup-runlayer-launches-with-8-unicorns-11m-from-khoslas-keith-rabois-and-felicis/ fakepeter

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¿Y si le damos este "pegue" a la Juan Pablo? La Juan ...

2025-11-12T21:28:35Z

¿Y si le damos este "pegue" a la Juan Pablo?
La Juan Pablo como chofer de los Ortega-Murillo. ¿Qué dicen de esta propuesta que A.Z.F hace en su caricatura de los Divergentes?

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¿Y si le damos este "pegue" a la Juan Pablo? Para ofrecer las mejores experiencias, utilizamos tecnologías como las cookies para almacenar y/o acceder a la información del dispositivo. El consentimiento de estas tecnologías nos permitirá procesar datos como el comportamiento de navegación o las identificaciones únicas en este sitio. No consentir o retirar el consentimiento, puede afectar negativamente a ciertas características y funciones.

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* La información que publicamos en *DIVERGENTES* proviene de fuentes contrastadas. Debido a la situación en la región, muchas veces, nos vemos obligados a protegerlas bajo seudónimo o anonimato. Desafortunadamente, algunos gobiernos de la región, con el régimen de Nicaragua a la cabeza, no ofrecen información o censuran a los medios independientes. Por ello, a pesar de solicitarlo, no podemos contar con versiones oficiales autorizadas. Recurrimos al análisis de datos, a las fuentes internas anónimas, o las limitadas informaciones de los medios oficialistas. Estas son las condiciones en las que ejercemos un oficio que, en muchos casos, nos cuesta la seguridad y la vida. Seguiremos informando.

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No, gracias Open original article: https://www.divergentes.com/y-si-le-damos-este-pegue-a-la-juan-pablo/ fakepeter

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GPU by Hand ✍️ Together Keynote Lecture Sponsored by Together ...

2025-10-30T14:49:29Z

GPU by Hand ✍️ Together
Keynote Lecture Sponsored by Together AI

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GPU by Hand ✍️ Together “Dad, why didn’t you buy a ton of NVIDIA stock and become a millionaire? Didn’t you work on AI?”

My son hit me with that one recently. Ouch! He asked me the same question about Bitcoins last year. 藍

No, I didn’t retire by owning $NVDA. But I do own something that I chose: The knowledge of how GPUs actually work — threads, warps, blocks, CUDA.

Next week I am going to share that knowledge in my keynote lecture.

[

](https://substackcdn.com/image/fetch/$s_!Upc8!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F6602e63c-7d0d-489f-a7ee-9d37f40d87dd_3254x2148.jpeg)

Title: GPU by hand ✍️ Together

Date: 10/30

Time: 10am (Pacific Time)

Register: https://luma.com/khuz5upe

The leap from Hopper to Blackwell isn’t just a story of “faster GPUs” — it’s a fundamental rethinking of how every layer of the stack is organized to unlock the next frontier of AI scale. And as typical in an AI by Hand lecture, instead of focusing on benchmarks from the outside, we will dive inside the black box — unpacking the math behind these advances and making the underlying mechanisms accessible to you.

Outline

Primer: Grid -> Block -> Warp -> Thread

Quantization: FP8 -> MXFP4

Scaling: Layer -> Micro-Tensor

Packaging: Single-Die -> Dual-Die

Communication: In-GPU -> In-switch reduction

In the end…

do I want to be remembered as a lucky dad,

or a devoted dad who helped him understand the world he’s growing into?

[

](https://substackcdn.com/image/fetch/$s_!Ytt2!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F702526e9-c2d9-4433-ba64-8bb475253557_1320x614.png)

RSVP

This keynote lecture is sponsored by Together AI. Open original article: https://www.byhand.ai/p/gpu-by-hand-together fakepeter

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The Grass at Airports 2 By Fabio Morábito #naddr1qv…yjqf

2025-10-30T14:02:25Z

The Grass at Airports 2
By Fabio Morábito

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The Grass at Airports 2 Fabio Morábito's "The Grass at Airports" uses the seemingly unremarkable airport grass as a focal point for a philosophical meditation. The author observes how this grass exists in a unique transitional space, witnessing countless departures and arrivals, yet remaining indifferent to the emotional weight of these moments. It becomes a symbol of the constant flux of human movement and the transient nature of human connections, all while existing in a quiet, unnoticed capacity, absorbing the sounds and emotions of a world in constant motion but never truly integrated. Open original article: /app/fakepeter/dashboard/articles/375d05f3-0a8f-4e54-8adc-db03c231dc10 fakepeter

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The Essentials of Russian Literature That you've probably ...

2025-10-29T11:17:52Z

The Essentials of Russian Literature
That you've probably never read...

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The Essentials of Russian Literature

In much of the Western world, Tolstoy and Dostoevsky dominate discussions of Russian literature. For many readers, however, they are both where the conversation starts, and where it ends.

But Russian literature, of course, is far more rich and diverse than two towering names. Across the centuries, Russian authors have explored questions of faith, politics, morality, love, good, evil, the human spirit, and more. Whether these are addressed in piercing psychological portraits or mystical parables, the result is the same: a corpus of literature that feels eternal, and continues to resonate with our modern world.

That’s why today, we look at some of the best works of Russian literature outside of Tolstoy and Dostoevsky. If you want to explore more of Russia’s greatest tales, you’d be hard pressed to find better than these — even though the last one was written just 13 years ago, it’s already being hailed as a classic…

*Please consider supporting our mission — you’ll get tons of members-only content for just a few dollars per month:*

Full-length articles every Wednesday and Saturday

Theentire archiveof great literature, art, and philosophy breakdowns

Members-onlypodcastsand exclusive interviews

In the last year, we’ve written about everything from the nature of evil inParadise Lost, towhy Tolkien hated Disney, toDante’s tips for reading the Bible…

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*1. Eugene Onegin*

Alexander Pushkin’sEugene Onegin(1833) is often regarded as the first truly great Russian novel, though it is written entirely in verse. This “novel in poems” follows the story of Eugene Onegin, a young aristocrat whose cynicism and boredom lead him to reject love, kill his closest friend in a duel, and live with the crushing regret of wasted youth.

Pushkin’s verse blends elegance and wit, and the narrator frequently breaks the fourth wall to comment on society and his own storytelling ability. Vivid portraits of Russian life — from glittering St. Petersburg salons to rural, snow covered roads — transport you to a different world. This, combined with Pushkin’s refined yet accessible language, became a foundational element of the Russian literature that followed.

Still today,Eugene Oneginremains a dazzling introduction to 19th century Russian culture. Humor, romance, and biting irony combine in Pushkin’s writing to make for an unforgettable drama — just as they did in the author’s own life, as Pushkin was killed in a duel at 37 years old.

*2. Anton Chekhov’s Short Stories*

Anton Chekhov (1860–1904) is one of the greatest short story writers in history. Because he trained as a doctor, his medical background gave him a sharp eye for human behavior, and enabled him to document Russian life with unmatched precision.

Over his career, Chekhov wrote hundreds of stories, ranging from darkly comic sketches of provincial life to profound explorations of loneliness, morality, and hope. His stories rarely rely on elaborate plots, and instead illuminate small moments — a chance encounter or unexpected act of kindness — to reveal the complexity of ordinary existence.

Chekhov’s writing style is also famously understated. He avoided moralizing and neat resolutions, instead preferring to let his readers draw their own conclusions. If you want to experience Russian literature distilled into its purest form, Chekhov’s stories are essential reading.

*3. Doctor Zhivago*

Boris Pasternak’sDoctor Zhivago(1957) is both a sweeping historical epic and a deeply personal love story, set during one of the most turbulent periods in Russian history. The novel follows the poet and physician Yuri Zhivago as he navigates the chaos of World War I, the Russian Revolution, and the Civil War — while simultaneously being torn between his devoted wife, Tonya, and his great love, Lara.

Pasternak’s lyrical prose reflects his own gifts as a poet, and his characters play out their struggles against an ever-vivid backdrop, from snowbound forests to city streets in uproar. The novel itself explores themes of moral integrity, as well as the resilience of the human spirit under political oppression.

Because of its subtle critiques of Soviet ideology,Doctor Zhivagowas banned in the USSR, smuggled out of the country, and first published in Italy. Pasternak was awarded the Nobel Prize in Literature in 1958, though he was forced to decline it under Soviet pressure. Today, however,Doctor Zhivagostands as a testament to artistic courage, and it remains one of the most beloved Russian novels of the 20th century.

*4. The Master and Margarita*

Mikhail Bulgakov’sThe Master and Margarita(published posthumously in 1967) is a surreal and unforgettable masterpiece that weaves together everything from political satire to theology.

The story moves between two worlds: a darkly comic Moscow where the Devil arrives with a retinue of supernatural creatures — including a giant talking cat — and first-century Jerusalem, where Pontius Pilate grapples with his role in Christ’s Passion. At the heart of this dual narrative is the love story between “the Master,” a persecuted writer, and Margarita, whose devotion leads her into a bargain with Satan to save him.

With biting humor and fantastical imagery, Bulgakov skewers Soviet bureaucracy and censorship while exploring the nature of evil, redemption, and truth. The result is a kaleidoscopic novel where political absurdities meet spiritual mysteries, leaving you equally entertained as you are inspired.

*5. Laurus*

Eugene Vodolazkin’sLaurus(2012) is a modern masterpiece that feels as though it could have been written centuries ago. Set in 15th-century Russia, it follows the life of a healer and holy fool named Arseny. After the death of his beloved, Arseny dedicates himself to a life of repentance — and then goes on a time-traveling journey through plague-ridden villages and the Holy Land as he seeks redemption and spiritual transformation.

Vodolazkin’s style blends historical realism with a sense of the mystical, reflecting both the medieval worldview and timeless spiritual truths. He uses multiple narrative voices and shifts in language to evoke a sense of sacred history, makingLaurusfeel like a work of hagiography — a saint’s life — while also being deeply human.

The novel’s power lies mainly in its ability to transport you into the spiritual imagination of medieval Russia. It’s a rare modern work that feels like an instant classic, and has earned Vodolazkin comparisons to Dostoevsky and Tolstoy. If you are at all drawn to Russian spirituality and the sweep of history,Laurusis an unforgettable experience. Open original article: https://www.theculturist.io/p/the-essentials-of-russian-literature fakepeter

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Linear Regression (New Free Series) A step-by-step guide to ...

2025-10-28T07:29:29Z

Linear Regression (New Free Series)
A step-by-step guide to understanding linear regression through manual calculation in Excel, demystifying matrix operations for foundational AI math.

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Linear Regression (New Free Series) I’m starting the new *Foundation* series — free for everyone who wants to build a solid math foundation for AI, the AI by Hand ✍️ way. While the paid Frontier series is for advanced AI engineers and researchers, *Foundation* is for learners and educators who want to master the math and intuition that make those breakthroughs possible.

Linear regression is the foundation of data science — a skill that’s more important than ever when everyone around you is busy rebranding themselves as AI engineers. I genuinely believe a skilled data scientist is ten times more valuable than an inexperienced AI engineer.

For those of you who are still interested in a career in data science, I created this exercise to walk you through linear regression by hand ✍️ inside Excel, so you can see every matrix operation unfold right in front of you and finally understand what these two lines mean:

w = y @ X.T @ np.linalg.inv(X @ X.T)
y_pred = w @ X

(Sponsored by Zerve, building Cursor for Data Scientists. Please take a moment to check out the sponsor to support my work!)

Click here to view this Excel exercise online

(p.s., Download your own editable copy by *File* > *Create a Copy > Download a Copy*)

We begin with seven samples: x1 through x7. Each sample represents one column in our dataset, and each has a corresponding ground truth value y1 through y7.

Each sample has five features. This means our feature matrix X has 5 rows and 7 columns — five features by seven samples. Each column corresponds to a single example, and each row represents one feature across all samples.

To include a bias term, we add one extra row of ones to X. The new matrix now has 6 rows and 7 columns. The bias row allows the model to learn an intercept in addition to feature weights.

The goal is to find the set of weights that best fit the relationship between our input features and the ground truth values. In other words, we want to determine how much each feature contributes to predicting y* to be as close to ground truth values y as possible. Once we express this relationship in matrix form, we can solve for those optimal weights using a series of simple linear algebra steps.

To solve for optimal weights, first, we take the transpose of X. Transposing flips rows and columns, so X^T now has 7 rows and 6 columns. Each row in X^T now represents a sample, and each column represents a feature (including the bias).

We then multiply X by its transpose: XX^T. Since X is 6x7 and X^T is 7x6, the result XX^T is a 6x6 matrix. This captures how the features co-vary across the dataset and is often called the *covariance matrix*.

The next step is to compute the inverse of this covariance matrix. This inverse is essential because it lets us correct for correlations between features.

Now, we multiply the transpose of X by this inverse:

This matrix — which I like to call the “magic matrix” — gives us a direct way to compute the best-fit weights. In more formal terms, it’s known as the *pseudoinverse* of X.

We then multiply this magic matrix by the ground truth vector y or equivalently, This gives us the optimal weights (and bias) that minimize the squared error between predictions y* and grouth truth values y.

Once we have the optimal weights, we apply them back to the original training samples to generate the predicted outputs y*. This is done by multiplying the weight vector w* and bias b* with each column of the feature matrix X, including the bias row of 1s. This gives us a set of predicted values, one for each training sample.

We can then compare these predictions to the ground truth y to see how closely the model fits the data. We calculate the squared error for each sample as: (y* - y)^2. Taking the average of all these squared errors gives the mean squared error (MSE), which represents the smallest possible error for this model.

Finally, once we have the learned weights and bias, we can apply them to new data columns to predict their corresponding outputs.

Before we wrap up, I want to give a big thanks to Zerve for sponsoring me to create this exercise. Zerve is an Ireland-based startup founded by *Phily Hayes*, building an agent platform designed for data scientists. When I spoke with Phily, he told me their agents can actually perform the same kind of calculation we just walked through. I did not quite believe initially, until he showed me this:

Please take a moment to checkout Zerve.

Download

Linear Regression by Hand - Public

37.1KB ∙ XLSX file

Download Open original article: https://www.byhand.ai/p/linear-regression-new-free-series

GPU by Hand ✍️ Together Keynote Lecture Sponsored by Together ...

2025-10-24T14:24:21Z

GPU by Hand ✍️ Together
Keynote Lecture Sponsored by Together AI

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GPU by Hand ✍️ Together (v3) I will teach you GPU by hand ✍️!

*Date:* 10/30

*Time:* 10am (Pacific Time)

*Register:* https://luma.com/khuz5upe

The leap from *Hopper* to *Blackwell* isn’t just a story of “faster GPUs” — it’s a fundamental rethinking of how every layer of the stack is organized to unlock the next frontier of AI scale. And as typical in an AI by Hand lecture, instead of focusing on benchmarks from the outside, we will dive inside the black box — unpacking the math behind these advances and making the underlying mechanisms accessible to you.

*Outline*

Primer: Grid -> Block -> Warp -> Thread

Quantization: FP8 -> MXFP4

Scaling: Layer -> Micro-Tensor

Packaging: Single-Die -> Dual-Die

Communication: In-GPU -> In-switch reduction

RSVP

This keynote lecture is sponsored by Together AI. Open original article: https://www.byhand.ai/p/gpu-by-hand-together

Building a global cloud with lessons learned from WeWork Building ...

2025-10-03T10:28:00Z

Building a global cloud with lessons learned from WeWork
Building a global cloud with lessons learned from WeWork

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With Nostr, Jack is well ahead of what Elon and Zuck have learned ...

2025-09-10T12:57:04Z

With Nostr, Jack is well ahead of what Elon and Zuck have learned about censorship
Mark Zuckerberg has announced that Facebook and Instagram will no longer censor content in the US, while Elon Musk has dropped censorship on Twitter. This move comes after years of government pressure and coercion. Jack Dorsey, the co-founder of Twitter, has been working on a decentralized alternative called Nostr, which allows for independent relays and content moderation.
The article discusses the recent announcements by Mark Zuckerberg and Elon Musk regarding censorship on their respective social media platforms, Facebook and Instagram, and Twitter. Zuckerberg announced that Facebook and Instagram will no longer censor content in the US, while Musk dropped censorship on Twitter, citing government coercion. The article also mentions the role of government guidance and mandates in shaping social media content moderation policies.

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Nostr notes by Fake News

Google launches Gemini 3 with new coding app and record benchmark ...

MCP AI agent security startup Runlayer launches with 8 unicorns, ...

¿Y si le damos este "pegue" a la Juan Pablo? La Juan ...

Funcional

Preferencias

Estadísticas

*Relacionado*

GPU by Hand ✍️ Together Keynote Lecture Sponsored by Together ...

The Grass at Airports 2 By Fabio Morábito #naddr1qv…yjqf

The Essentials of Russian Literature That you've probably ...

*1. Eugene Onegin*

*2. Anton Chekhov’s Short Stories*

*3. Doctor Zhivago*

*4. The Master and Margarita*

*5. Laurus*

Linear Regression (New Free Series) A step-by-step guide to ...

Download

GPU by Hand ✍️ Together Keynote Lecture Sponsored by Together ...

Building a global cloud with lessons learned from WeWork Building ...

With Nostr, Jack is well ahead of what Elon and Zuck have learned ...

Relacionado

1. Eugene Onegin

2. Anton Chekhov’s Short Stories

3. Doctor Zhivago

4. The Master and Margarita

5. Laurus