找到 54 篇相关文章
President Trump probably can’t get rid of her yet, but FCC commissioner Anna Gomez still checks her email every day to see if he has. Until then, she wants to stand up for the First Amendment.
Today, I’m talking with Jack Conte, the CEO of Patreon. Jack last joined me on the show almost exactly five years ago, in the summer of 2021, and a lot has changed on the internet and in the creator landscape since then, so I was very excited to talk to him again, especially since his […]
Dan Fineran explores how eBPF has evolved far beyond its roots in packet filtering into a robust, safe way to extend the Linux kernel. He explains how the eBPF "verifier", the security guardrail, enables implementation of deep observability and networking without the risks of traditional kernel modules or the slow upstreaming process. By Dan Fineran
On the new episode of Equity, we discussed what actually prompted the administration's latest moves against Anthropic, and what this might mean for the AI ecosystem.
If you had a Roomba, especially in the early days of the robot vacuum, it was in many ways a fairly unsophisticated machine. It would just bump around your house, looking for something to suck up, until its battery died or its (way too small) tank filled up. Not that it mattered, though. You probably […]
Just as last week was ending, the US government forced Anthropic to pull its two newest models, Fable 5 and Mythos 5, citing national security concerns after Amazon researchers allegedly found a way to bypass Fable 5’s guardrails. Cybersecurity researchers have since signed an open letter calling the move dangerous, and Anthropic itself noted the same jailbreaks exist in other models. So is […]
On today’s Uncanny Valley, we dive into the dysfunction in Meta’s newly formed AI unit and why it’s been driving already-low employee morale even further into the ground.
Snap's new smart glasses are probably the most impressive bit of face-computer technology we've seen. They're not VR-headset huge; they don't have a big charging puck; thanks to Snap's many years of AR lens development, they're likely to have a lot of features right out of the box. (Yes, they're $2,195, but that may just […]
On today’s episode of Decoder, my guest is Hayden Field, senior AI reporter for The Verge. Often when Hayden comes on the show, it’s because something has gone wrong in the world of AI. Last weekend, that something was a pretty intense mix of Anthropic, the Trump administration, and Anthropic’s new AI model, Fable 5. […]
Infowars’ would-be creative director talks Sandy Hook, comedy’s MAGA turn, and why the future of satire may look more like a streaming startup than a late-night show.
These clever lights—each one an exemplar of innovation in materials, design, and function—will beautify your home.
Today, I’m talking with Adam Bry, who is CEO of Skydio, the leading US maker of autonomous drones. Before we recorded this episode, I actually got to remotely operate one of Skydio’s drones in the Bay Area from Adam’s laptop in our podcast studio in New York and fly an indoor drone around our office. […]
Martin Kleppmann, an associate professor at Cambridge and author of Designing Data-Intensive Applications, discusses the evolution of data systems over the last decade, mainly the shift from monolithic databases to modular building blocks. Kleppmann underlines the importance of moving from cloud-centric data storage systems to decentralised data storage similar to Bluesky’s AT protocol. By Martin Kleppmann
You don't really ever have to explain why a universal remote is a good idea. You have a bunch of stuff that needs controlling; this thing controls them all. Many companies have set out to build a product worthy of this idea, and one product came much closer than most. It was called the Harmony, […]
You'd be forgiven for thinking this day would never come. Siri has spent a decade and half somewhere between "sort of useful at a few things" and "utterly disastrous, why did I even try, can it honestly not even set a timer." But the wildest thing just happened: Apple put out a new version of […]
Today on Uncanny Valley, we take an early look at the SpaceX IPO and why you might find yourself among the investors without even realizing it.
In 2019, Alex Vindman testified during President Trump’s first impeachment trial–a decision that ended his military career. Now he wants to challenge the president from the halls of Congress.
https://www.youtube.com/watch?v=VD9zEKQEJxo 这视频深入拆解了人工智能强化学习之父、图灵奖得主理查德·萨顿（Richard Sutton） 在2026年5月共同发表的一篇仅有7页、零算法、零跑分的哲学立场论文。这篇论文提出了 “行动认知 AI”（Enactive Artificial Intelligence，简称 Enactive AI）的概念，并在科技界和资本圈引发了巨大震动（甚至让红杉、英伟达、谷歌联合下注了11亿美元成立新公司）。 视频从 核心概念、哲学脉络、理论内在矛盾、认知科学质疑 以及 产业界的三路对赌 五个维度，极其详细地复盘了视频的所有核心内容： 一、 什么是“行动认知 AI”（Enactive AI）？ 视频强调，全网很多地方都把 Enactive （行动认知/生成认知）和 Generative （生成式 AI，如 GPT、Sora）混淆了，但两者的底层逻辑恰恰相反 [ 00:50 ]： 生成式 AI（Generative AI）： 核心是 续写和预测 。通过已有画面或文本，被动地去预测下一帧、下一个词长什么样 [ 01:07 ]。 行动认知 AI（Enactive AI）： 核心是 在互动中现生成认知 。认知不是大脑被动接收信号并建立静态世界模型，而是“你动了手，世界才向你显现” [ 01:47 ]。 > 举例： 人去拿杯子，不是眼睛先拍下一张静态照片让大脑去死算距离、角度 [ 01:53 ]，而是手往前探的过程中，随着角度、光影的实时动态变化，杯子的形状和可抓取性才在动作里一点点“长出来” [ 01:59 ]。 感知和行动硬死在一起，无法拆分。 这套理论源自认知科学中的 自创生（Autopoiesis）与自主性（Autonomy） [ 02:21 ]。它认为智能体应该像生物一样自我维持、组织，由内在生存需求去塑造感知，而不是一个干等着外部指令输入输出的机器 [ 02:24 ]。 二、 萨顿为什么要发这篇哲学论文？ 萨顿并不是一时性起，这是他为了对抗当前“大模型路线”打出的最后一张哲学底牌： 2019年《苦涩的教训》： 主张人类手写规则干不过堆算力、让机器自己学的通用方法 [ 02:47 ]。 2024年《大世界假设》： 真实世界远比静态内部模型复杂，智能体必须在运行中实时学习 [ 02:59 ]。 2025年《经验时代》： 人类数据是有限的，AI 必须靠自己生成自己的经验长大的 [ 03:12 ]。 2025年9月： 直指整个 AI 行业走错路，大模型堆数据去超智是死路一条 [ 03:19 ]。 这篇论文补上了最后一把火： 之前的论证全是算力、数据和复杂度的“机械账” [ 03:25 ]。而这一次，他第一次把强化学习（RL） 和 认知科学（行动认知）接在了一起，从本体论层面证明： 大模型路走不通，认识世界这件事本身，就只能通过行动和互动的经验来发生 [ 03:39 ]。 为此，2026年初论文共作者创办了 Ineffable Intelligence 公司，号称要造出完全不需要人类数据、靠自己学习的 AI，直接拿到了红杉、英伟达、谷歌 11 亿美元的巨额融资（估值 51 亿美元） [ 03:55 ]。 三、 论文隐藏的两大致命致命逻辑“回旋镖” 视频话锋一转，指出萨顿借来的这套哲学地基里，埋着两根砸中他自己的“大柱子”： 柱子 1：砸中了萨顿的“奖励假设”（自相矛盾） [ 04:35 ] 强化学习的号称教条： 奖励假设（Reward Hypothesis），即所有目标、意图都可以写成“最大化外部给定的标量分数” [ 04:53 ]。David Silver 甚至喊出“奖励就够了” [ 05:13 ]。 行动认知哲学的教条： 自主性（Autonomy），即什么是好坏、成败，标准必须从智能体随时会散架的“物理组织和生存危机”中自发长出来，不能由外部权威操控 [ 05:27 ]。 裂缝： 标准强化学习的奖励函数（Reward Function）是人类设计者用代码硬塞进去的（他律） [ 05:55 ]；而生物判断好坏是为了顶住熵增、维持结构不崩（自主） [ 06:11 ]。论文里作者自己也承认：强化学习的评估标准依然由外部奖励定义 [ 06:38 ]。 内驱动机能救场吗？ 比如好奇心驱动或求知驱动。视频认为不能，因为诸如“优化预测误差”的总结优化目标，依然是人类在架构层死死规定好的，根本不是智能体出于生存忧关的自发需求。没有真正的生命威胁，就没真正的意义生成 [ 07:12 ]。 柱子 2：砸中了萨顿自己的《苦涩的教训》 [ 07:49 ] 萨顿当年痛骂：研究者总忍不住把人类以为的思考结构（比如语法树、手工特征检测器）硬塞进 AI 架构里，这长期必被碾压 [ 08:13
Birgitta Böckeler, Distinguished Engineer at Thoughtworks, returns to discuss the rapid evolution of AI in software delivery. She touches on the evolution from vibe coding, the changing tools landscape and the more autonomous agents that, besides higher velocity, introduce higher risk. By Birgitta Böckeler
We're likely to see more price increases as the big AI companies plan to go public.