Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog

Category: robotics/AI – Page 11

Kendall Haven on Story Proof: The Science Behind Story

Six months before ChatGPT arrived, I sat down for two and a half hours with the only West Point graduate ever to become a professional storyteller.

Dr. Kendall Haven also holds a doctorate in oceanography and spent eight years as a senior research scientist at the Department of Energy. Then he walked away to chase what he calls a very different kind of truth.

His bottom line stopped me cold:

“Story is not theoretical anymore. It’s not hyperbole. Story is woven into our DNA. We are story. That’s now science.”

In 2022, that sounded like a storyteller defending his craft. Today, with machines built entirely out of human language, it sounds like something else.

Kendall argues that your brain story-processes information before it ever reaches your conscious mind. Which is why throwing more #data at people almost never changes their behavior. You have to reframe the story instead. And the most effective change stories, he says, are not about change at all. They’re about preservation.

Continue reading “Kendall Haven on Story Proof: The Science Behind Story” | >

Spiking neural network learns to predict what will happen, when, and how likely it is

Imagine hearing a familiar sound and expecting something to happen. Before the event arrives, the brain can predict what it will be, when it will occur and how likely it is. Yet computational models often treat these questions separately or use learning methods that are difficult to reconcile with biological circuits. A new study proposes an alternative in which one population of spiking neurons learns all three together.

The research team was led by Associate Professor Zenas C. Chao along with Yohei Yamada, an academic specialist, from the International Research Center for Neurointelligence (WPI-IRCN), UTIAS, The University of Tokyo, Tokyo, Japan.

The researchers developed a recurrent spiking-network model to test whether a single neural population could learn event identity, timing and probability using local learning rather than backpropagation or a globally broadcast error signal. The study is published in Communications Biology.

Bitdefender alerta de una campaña global de malware preinstalado en teléfonos Android

La compañía ha identificado Midnight Mimosa, una operación activa desde hace dos años que infecta miles de dispositivos en más de 150 países antes incluso de su primer encendido. El malware, integrado en el firmware, ejecuta fraude publicitario, recopila datos y permite controlar los teléfonos de forma remota.

Advancing mathematics research with AI-driven formal proof search

For decades, mathematicians have dreamed of a world where computers could do more than just crunch numbers—where they could actually think, reason, and help discover new truths. A major hurdle, however, has been the notorious “hallucination” problem of artificial intelligence: large language models (LLMs) are great at sounding confident, but they frequently make mathematical errors, making them unreliable for serious research.

Now, a groundbreaking study by researchers including Tsoukalas et al., published in Science, has shattered that barrier by combining the creative writing power of AI with the ruthless accuracy of a mathematical referee.

Their system—called AlphaProof Nexus—pioneers a new way of doing math by teaming up an AI with a specialized computer program called Lean is a “formal proof assistant,” a piece of software that acts as the ultimate skeptic. It doesn’t accept a mathematical proof unless every single logical step is airtight and verified by its strict compiler.

The endless loop of creativity and proof.

The magic of AlphaProof Nexus lies in its teamwork model:

1. The AI brainstorms: The large language model acts as the creative mathematician, generating ideas, strategies, and formal proofs in the Lean language.

2. The computer checks: The Lean compiler instantly tests the AI’s work. If there’s even a tiny flaw in the logic, it rejects it and points out why.

Continue reading “Advancing mathematics research with AI-driven formal proof search” | >

Remember Orkut? Its founder wants to bring it back

In a post on X on Thursday, Orkut Büyükkökten, the founder of the eponymous social network, urged users to visit Orkut.com and add their names in support of bringing it back, as well as invite others to join.

Orkut first debuted in 2004 as a side project by Büyükkökten, 51, while he was at Google. The social network went on to become hugely popular in India and Brazil but later lost ground to Facebook. Google eventually shut it down in September 2014, shifting its focus to other platforms, including Google+ and YouTube.

In a letter published on Orkut.com, Büyükkökten criticized how social media has evolved over the past two decades, particularly the growing influence of algorithms and AI-generated content. “Artificial intelligence is extraordinary technology, but it’s dissolving the one premise that made social networking special and worth building: that there was a person on the other side,” he wrote.

The Steel Was Never Real

7 review: how falling walls between science, bodies, and AI are changing everything.

https://youtu.be/tNXNZLZI7Us](https://youtu.be/tNXNZLZI7Us)

*Oct 10, 2026 • S7 E75 • 50:52*

What if the walls between the sciences were never real? 🗄️🔥

After 75 deep dives, Heliox found a hidden pattern: the best answers live in the overlap between disciplines.

In “The Steel Was Never Real,” you’ll hear:

• How a Bayesian model revealed that two identical heart attacks can have completely different biological causes.

Continue reading “The Steel Was Never Real” | >

Microsoft and Nvidia Join Forces to Reshape the PC

Microsoft and Nvidia took the stage together at a Windows event in San Francisco on October 8 to unveil the next phase of the personal computer. In a rare joint appearance, the two companies’ CEOs announced a sweeping collaboration spanning operating system security architecture to hardware design, with the goal of making AI agents the core computing entities within the Windows ecosystem.

Nvidia CEO Jensen Huang made clear during the conversation that the personal computer, once a tool for humans, will in the future serve both people and AI agents. He pointed out that agents have the potential to utilize software capabilities far more fully than humans, since users typically only know 10% to 15% of an application’s features, whereas an agent can master every function.

Microsoft CEO Satya Nadella framed the collaboration as a paradigm shift in computing. He noted that when agents begin directly manipulating files, applications, and cloud services, the operating system must be redesigned to allow agents to execute tasks safely and efficiently.