Good morning and Happy Friday! Karen Hao's explosive Atlantic excerpt reveals the chaos behind Sam Altman's brief 2023 ouster, including how OpenAI's chief scientist once discussed building "bunkers" before releasing AGI. The $300 billion company that began as an idealistic nonprofit is now the centerpiece of an "empire of AI".
— The Deep View Crew
In today’s newsletter:
- 🌧️ AI for Good: AI-powered local weather forecasting model
- 🤯 Another week, another Google AI drop
- 🧠 Could AI double human lifespan by 2030?
🌧️ AI for Good: AI-powered local weather forecasting model
Source: YingLong
AI is helping forecast local weather faster and more precisely with a new model called YingLong.
Built on high-resolution hourly data from the HRRR system, YingLong predicts surface-level weather like temperature, pressure, humidity and wind speed at a 3-kilometer resolution (which means 3km x 3km coverage). It runs significantly faster than traditional forecasting models and has shown strong accuracy in predicting wind across test regions in North America.
Dr. Jianjun Liu, a researcher on the project, explains that “traditional weather forecasting solves complex equations and takes time. YingLong skips the equations and learns directly from past data. It’s like giving the model intuition about what’s likely to happen next.”
Why it matters: Local weather forecasting requires more precision than broad national models can offer. That’s where limited area models (LAMs) come in. While most AI research has focused on global weather systems, YingLong brings that power to cities and counties in a faster, more focused way.
- Traditional weather models can take hours or days to compute.
- YingLong delivers accurate local forecasts in much less time.
- Faster forecasts help cities and agencies respond to storms and plan ahead with greater confidence.
YingLong combines high-resolution local data with boundary information from a global AI model called Pangu-Weather. It focuses its predictions on a smaller inner zone to reduce computing power and improve speed. It predicts 24 weather variables with hourly updates and performs especially well in surface wind speed forecasts. Improvements in temperature and pressure forecasts are underway using refined boundary inputs.
Big picture: AI models like YingLong won’t fully replace traditional forecasting yet, but they’re already making forecasting faster and more efficient. By offering high-resolution predictions without the usual computing demands, these tools can help more people make better decisions about weather so you don’t get rained out at the next Taylor Swift concert.
Seamlessly connect your AI agents with external tools
Not-so-fun fact: Less than two-fifths of AI projects go into production.
Why? Simple. Because building real-world AI agents is hard – and that’s before you even start worrying about things like bespoke tool integrations. Lucky for you, there’s a simple and powerful solution… Outbound Apps from Descope.
- Connect your AI agent with 50+ external tools using prebuilt integration templates
- Request data and scopes from third-party tools on users’ behalf
- Store multiple tokens per user with different scopes, calling each token as needed
And best of all, it requires no heavy lifting from your developers. Start using Outbound Apps right here when you create a free Descope account – no credit card required.
🤯 Another week, another Google AI drop
Source: Google
Google marked Global Accessibility Awareness Day by rolling out new AI-powered accessibility features across Android and Chrome. The updates bring Google’s latest Gemini AI model into everyday tools.
- TalkBack + Gemini — Ask your screen reader what’s in an image and get an answer on the spot.
- Expressive Captions — Live Caption now supports stretched-out sounds like “gooooal” in a sports clip or noting background noises like whistling
- Page Zoom — A slider scales text up to 300% in Chrome on Android without wrecking layouts.
- Scanned‑PDF OCR — Chrome desktop automatically reads text in scanned PDFs so screen readers can copy or search it
Google is expanding its work with Project Euphonia by open-sourcing tools and datasets on GitHub. These tools help developers train models for diverse and non-standard speech. In Africa, Google.org is supporting the Centre for Digital Language Inclusion to create new speech datasets in 10 African languages and support inclusive AI development.
In other Google news, Google’s DeepMind research lab has unveiled AlphaEvolve, a Gemini-powered AI agent that autonomously evolves and tests code. The system combines Gemini 2.0 Flash and 2.0 Pro with automated code evaluation to iteratively improve algorithms. AlphaEvolve has already boosted the efficiency of Google’s data centers and chip design processes, and even discovered a faster method for matrix multiplication – solving a math problem untouched since 1969.
The continuous flow of announcements over the last couple of weeks underscores Google’s growing integration of AI into its entire $2T gambit of products.
Could This Company Do for Housing What Tesla Did for Cars?
Most car factories like Ford or Tesla reportedly build one car per minute. Isn’t it time we do that for houses?
BOXABL believes they have the potential to disrupt a massive and outdated trillion dollar building construction market by bringing assembly line automation to the home industry.
Since securing their initial prototype order from SpaceX and a subsequent project order of 156 homes from the Department of Defense, BOXABL has made substantial strides in streamlining their manufacturing and order process. BOXABL is now delivering to developers and consumers. And they just reserved the ticker symbol BXBL on Nasdaq*
BOXABL has raised over $170M from over 40,000 investors since 2020. They recently achieved a significant milestone: raising over 50% of their Reg A+ funding limit!
BOXABL is now only accepting investment on their website until the Reg A+ is full.
Invest now before it’s too late
- Philips turns to Nvidia to build AI model for MRI
- AI and genetics are changing the way farmers grow corn
- AI twins have the potential to solve many problems
- Hedra lands $32M to build digital character foundation models
- Huawei’s newest watch has several must-see features
- Howie: Email based assistant to handle your calendar (in beta)
- Goldcast: Marketers are sitting on a goldmine of untapped content. Goldcast’s Content Lab helps you turn one video into 30+ assets—blogs, clips, posts, and more. Try it free*
- Aomni: Agents that help with sales
- Supermemory: Give your AI have ALL the info it needs
- Lex: Cursor, but for writing
The right hires make the difference.
Scale your AI capabilities with vetted engineers, scientists, and builders—delivered with enterprise rigor.
- AI-powered candidate matching + human vetting.
- Deep talent pools across LatAm, Africa, SEA.
- Zero upfront fees—pay only when you hire.
🧠 Could AI double human lifespan by 2030?
Source: ChatGPT 4o
In 1824, the average American lived just over 40 years. Two centuries later, that number has nearly doubled. The leap in life expectancy was driven mostly by reduced infant mortality and breakthroughs in public health and medicine. But even with antibiotics, vaccines, and surgery, the idea of living to 150 still sounds like science fiction. Now, a wave of researchers believes AI could make that fiction real.
One of the boldest voices is Dario Amodei, CEO of the AI company Anthropic. In October 2024, Amodei published a blog post predicting that AI would help double human lifespans to 150 by the end of this decade. Just three months later, he doubled down on stage at the World Economic Forum in Davos, claiming AI could deliver the breakthrough in just five years.
His reasoning? Humans already know of drugs that extend rat lifespans by 25 to 50 percent. Some animals, like certain turtles, live more than 200 years. If AI can discover and optimize therapies faster than any human team could before, why not us? Amodei believes once we hit 150, we could reach “longevity escape velocity” – the point where life-extending treatments advance faster than we age. In theory, that could allow people to live as long as they choose (better start a retirement plan for that second century of life).
He is not alone. Futurist Ray Kurzweil has made similar claims, predicting AI could halt aging by 2032. He points to two pathways. First, AI-designed nanobots that patrol the body to repair cells and deliver drugs. Second, the ability to upload the human brain into the cloud, preserving identity beyond biology. Kurzweil has long predicted the coming of a technological singularity. Longevity, in his view, may be the first step.
Yes, but…
Even believers admit these ideas are speculative. Many scientists are calling for caution. S. Jay Olshansky, a leading aging researcher and professor at the University of Illinois Chicago, says there is simply no evidence that AI can slow or stop the biological process of aging. Around the same time Amodei released his blog, Olshansky published a rebuttal in Nature Aging, arguing that enthusiasm is racing ahead of science.
“The longevity game we’re playing today is quite different from the one we played a century ago,” Olshansky wrote. “Now aging gets in the way, and this process is currently immutable.” He warns that claims about radical lifespan extension are not supported by evidence and are, in many ways, indistinguishable from pseudoscience.
Go deeper: AI is already helping improve human health. Researchers are using large models to develop drugs, predict protein structures, and model complex disease systems. Projects like DeepMind’s AlphaFold and Insilico Medicine are promising early examples. But increasing the healthspan – the number of years someone stays healthy – is not the same as increasing the lifespan. So far, no AI system has proven it can delay or reverse aging in humans.
The next leap may depend not on medicine alone but on machines. It is tempting to believe that AI will uncover the secrets of longevity. But believing and proving that are two very different things.
The search for longer, healthier lives is one of the noblest goals of science. AI could very well accelerate drug discovery, unlock hidden mechanisms of disease, and give every person access to high-quality health advice. That alone would be a transformative legacy.
Maybe the real question isn’t whether AI can help us live to 150. It’s whether we’d want to live that long (I don’t think I want to live to 150…) – and if we’re willing to put in the decades of work to find out.
Which image is real?
Login or Subscribe to participate in polls.
🤔 Your thought process:
Selected Image 1 (Left):
- “There are real 'faults' in the grass patterns in [this] video. In the [other] video the arc of the horizon does not look correct”
- “Wow. Video is very hard! I picked [this video] because the detail of the reflections through the trees and off the roof of the car as the camera moved seemed accurate - and like something AI wouldn't have totally nailed.”
Selected Image 2 (Right):
- “There was an odd vertical shadow in the road of the spinning camera view, that made it look like it had a gap where an AI forgot to render the yellow dotted line. But I've become too cynical - this was the real video!”
- “Shadow in the [other] one put me off”
💭 Thank you!
Thanks for reading today’s edition of The Deep View!
We’ll see you in the next one.
P.S. Enjoyed reading? Take The Deep View with you on the go! We’ve got exclusive, in-depth interviews for you on The Deep View: Conversations podcast every Tuesday morning. Subscribe here!
If you want to get in front of an audience of 450,000+ developers, business leaders and tech enthusiasts, get in touch with us here.
*Indicates sponsored content
*Boxabl Disclosure: This is a paid advertisement for BOXABL’s Regulation A offering. Please read the offering circular here. This is a message from BOXABL
*Reserving a Nasdaq ticker does not guarantee a future listing on Nasdaq or indicate that BOXABL meets any of Nasdaq's listing criteria to do so.
