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  • Phrack

    2 DAYS AGO

    1

    Phrack

    Phrack is legendary. It is the oldest, and arguably the most prestigious, underground hacking magazine in the world. It started in 1985 and is still running today. In this episode we interview the Phrack staff to hear some stories about what it’s like running a hacker magazine for 40 years. phrack.org SponsorsSupport for this show comes from ThreatLocker®. ThreatLocker® is a Zero Trust Endpoint Protection Platform that strengthens your infrastructure from the ground up. With ThreatLocker® Allowlisting and Ringfencing™, you gain a more secure approach to blocking exploits of known and unknown vulnerabilities. ThreatLocker® provides Zero Trust control at the kernel level that enables you to allow everything you need and block everything else, including ransomware! Learn more at www.threatlocker.com. Support for this show comes from Drata. Drata is the trust management platform that uses AI-driven automation to modernize governance, risk, and compliance, helping thousands of businesses stay audit-ready and scale securely. Learn more at drata.com/darknetdiaries. This episode is sponsored by Meter, the company building networks from the ground up. Meter delivers a complete networking stack - wired, wireless, and cellular - in one solution that’s built for performance and scale. Alongside their partners, Meter designs the hardware, writes the firmware, builds the software, manages deployments, and runs support. Learn more at meter.com.

    2 days ago

    •
    45 min
  • #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGI

    4 DAYS AGO

    2

    #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGI

    Nathan Lambert and Sebastian Raschka are machine learning researchers, engineers, and educators. Nathan is the post-training lead at the Allen Institute for AI (Ai2) and the author of The RLHF Book. Sebastian Raschka is the author of Build a Large Language Model (From Scratch) and Build a Reasoning Model (From Scratch). Thank you for listening ❤ Check out our sponsors: https://lexfridman.com/sponsors/ep490-sc See below for timestamps, transcript, and to give feedback, submit questions, contact Lex, etc. Transcript: https://lexfridman.com/ai-sota-2026-transcript CONTACT LEX: Feedback – give feedback to Lex: https://lexfridman.com/survey AMA – submit questions, videos or call-in: https://lexfridman.com/ama Hiring – join our team: https://lexfridman.com/hiring Other – other ways to get in touch: https://lexfridman.com/contact SPONSORS: To support this podcast, check out our sponsors & get discounts: Box: Intelligent content management platform. Go to https://box.com/ai Quo: Phone system (calls, texts, contacts) for businesses. Go to https://quo.com/lex UPLIFT Desk: Standing desks and office ergonomics. Go to https://upliftdesk.com/lex Fin: AI agent for customer service. Go to https://fin.ai/lex Shopify: Sell stuff online. Go to https://shopify.com/lex CodeRabbit: AI-powered code reviews. Go to https://coderabbit.ai/lex LMNT: Zero-sugar electrolyte drink mix. Go to https://drinkLMNT.com/lex Perplexity: AI-powered answer engine. Go to https://perplexity.ai/ OUTLINE: (00:00) – Introduction (01:39) – Sponsors, Comments, and Reflections (16:29) – China vs US: Who wins the AI race? (25:11) – ChatGPT vs Claude vs Gemini vs Grok: Who is winning? (36:11) – Best AI for coding (43:02) – Open Source vs Closed Source LLMs (54:41) – Transformers: Evolution of LLMs since 2019 (1:02:38) – AI Scaling Laws: Are they dead or still holding? (1:18:45) – How AI is trained: Pre-training, Mid-training, and Post-training (1:51:51) – Post-training explained: Exciting new research directions in LLMs (2:12:43) – Advice for beginners on how to get into AI development & research (2:35:36) – Work culture in AI (72+ hour weeks) (2:39:22) – Silicon Valley bubble (2:43:19) – Text diffusion models and other new research directions (2:49:01) – Tool use (2:53:17) – Continual learning (2:58:39) – Long context (3:04:54) – Robotics (3:14:04) – Timeline to AGI (3:21:20) – Will AI replace programmers? (3:39:51) – Is the dream of AGI dying? (3:46:40) – How AI will make money? (3:51:02) – Big acquisitions in 2026 (3:55:34) – Future of OpenAI, Anthropic, Google DeepMind, xAI, Meta (4:08:08) – Manhattan Project for AI (4:14:42) – Future of NVIDIA, GPUs, and AI compute clusters (4:22:48) – Future of human civilization

    4 days ago

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  • Moltbook Mania Explained

    1 DAY AGO

    3

    Moltbook Mania Explained

    A Reddit-style web forum for A.I. agents has captured the attention of the tech world. According to the site, called Moltbook, more than 1.5 million agents have contributed to over 150,000 posts, making it the largest experiment to date of what happens when A.I. agents interact with each other. We discuss our favorite posts, how we’re thinking about the question of what is “real” on the site, and where we expect agents to go from here.   Additional Reading: A Social Network for A.I. Bots Only. No Humans Allowed.Five Ways of Thinking About Moltbook  We want to hear from you. Email us at hardfork@nytimes.com. Find “Hard Fork” on YouTube and TikTok. Subscribe today at nytimes.com/podcasts or on Apple Podcasts and Spotify. You can also subscribe via your favorite podcast app here https://www.nytimes.com/activate-access/audio?source=podcatcher. For more podcasts and narrated articles, download The New York Times app at nytimes.com/app. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

    1 day ago

    •
    28 min
  • Vol. 160 一年多以后,再聊AI写代码Vibe Coding

    4 DAYS AGO

    4

    Vol. 160 一年多以后,再聊AI写代码Vibe Coding

    这都2026年2月啦😂!本来我们想策划做一个2025年的总结,但发现有点太难了,发生的事情特别多,而且年底又巨忙,最终我们就把Simon Willison的Blog post: The Year of LLMs结合我们自己过去一年的Vibe Coding经验聊了一期。提前祝各位听众姥爷们春节快乐哦🧨。 勘误: 节目中搞错宇宙科普节目YouTuber了,是Linvo不是司文,虽然我也看司文的视频但我想提的其实是Linvo😂 时间轴 00:00:00 播客主题从年度回顾 00:00:47 早期AI写代码的局限性 00:01:47 2025年AI编程进入YOLO模式 00:02:51 Simon Willison 大语言模型年度回顾 00:04:00 推理之年 (Year of Reasoning) 00:07:20 Agent之年 (Year of Agent) 00:10:05 Coding Agent的飞速发展 00:13:41 AI搜索的演变 00:14:28 AI搜索的挑战与风险 00:27:46 YOLO模式并非常态化,存在潜在风险 … Continue reading →

    4 days ago

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    2h 7m
  • The Evolution of Nigerian Fintech: Scale, Scars, and Strategy | Olu Akanmu

    1 DAY AGO

    5

    The Evolution of Nigerian Fintech: Scale, Scars, and Strategy | Olu Akanmu

    Why does Nigeria have 120 million people with digital identities but only 70 million with bank accounts? Despite a decade of growth, the "last mile" of financial inclusion remains a stubborn red ocean. Samora Kariuki sits down with Olu Akanmu, a rare leader who has navigated the "commercial battlefield" at the highest levels of telcos, Tier-1 banks, and scale-up fintechs (OPay). From his work with EFInA to his current role in academia at Lagos Business School, Olu brings a balanced perspective on why Nigeria’s fintech journey looks so different from the rest of the continent. This episode is a masterclass in the structural realities of the Nigerian market. Olu deconstructs the "Banking Lobby" that slowed mobile money, the friction between competing national identity systems (BVN vs. NIN), and why the next phase of fintech must move from simple payments to deep credit integration. He also provides a candid critique of "generic" late-stage fintech strategies and the internal politics that kill bank-led innovation. In This Episode, You Will Hear: The Banking Lobby vs. Telcos: A behind-the-scenes look at why mobile money struggled to launch in Nigeria and how fintechs filled the gap.The Prosperity Paradox: Why financial inclusion cannot scale in Northern Nigeria without solving for economic inclusion first.Digital Public Infrastructure (DPI): The missed opportunity of siloed identity and payment systems (BVN vs. NIN).Open Banking & the Credit Gap: Why payments grew 30% but credit only 4%, and how Open Banking can bridge that divide.Late-Stage Consolidation: Why "regulatory arbitrage" is ending and how fintechs must find "uncontested markets" to survive.The "Frigate Elephant" Problem: Why bank-led fintech subsidiaries often fail due to traditional banking mindsets.The "Peak Mobile Money" Myth: Why declining agent revenues are actually a sign of a maturing digital ecosystem. "Strategy begins with looking at your unique capabilities... You cannot come in as a late entrant offering a generic proposition and expect to scale in a contested market." Connect with Us: Samora Kariuki (Host): https://www.linkedin.com/in/samorakariuki/Olu Akanmu (Guest): https://www.linkedin.com/in/olu-akanmu-88280a/Frontier Fintech: frontierfintech.substack.com

    1 day ago

    •
    1h 14m
  • Episode 12 - State of the AI Industry

    19 JAN

    6

    Episode 12 - State of the AI Industry

    OpenAI CFO Sarah Friar and Khosla Ventures founder Vinod Khosla argue the greatest challenges in AI right now are keeping up with demand and making sure more people get the benefit. They unpack what's driving big investments in compute and why this moment is different from other technology cycles — with meaningful advances in health, agents, and robotics still ahead.  Chapters 00:00:00 — What’s the AI story of 2026? 00:07:28 — AI in healthcare 00:12:01 — Scaling compute to match revenue 00:18:05 — Difference between now and dot-com bubble 00:27:41 — Ads in ChatGPT 00:30:05 — Will consumers have more than one AI subscription? 00:36:41 — Winning in enterprise 00:39:44 — How can startups succeed? 00:44:05 — Robotics and beyond Hosted on Acast. See acast.com/privacy for more information.

    19 Jan

    •
    50 min
  • Prince Nwadeyi of SAG Ventures: Building solutions corporates need but won't execute themselves

    17/10/2025

    7

    Prince Nwadeyi of SAG Ventures: Building solutions corporates need but won't execute themselves

    Episode overview: Prince Nwadeyi spent years providing market research that unlocked South Africa's R600 billion (~USD 34.4 billion) informal economy for blue-chip clients. The likes of Swiss Re, Liberty, NASPERS all wanted the insights. Few wanted the execution risk. In conversation with Andile Masuku, Nwadeyi explains why his holding company SAG Ventures stopped selling insights and started building businesses. From Mustard Finance Group (formerly Setana Capital) providing working capital to township spaza shops (micro convenience stores), to Purchase Pal embedding funeral cover into everyday groceries, Nwadeyi's ventures share a common thread: aligning incentives across entire value chains whilst playing a longer game than quarterly-focused corporates can stomach. His journey from UCT postgrad researcher to operator deploying millions in credit with a claimed 99.9% repayment rate offers a masterclass in strategic patience and the power of granular consumer understanding. Key insights: - On why insights alone don't create impact: "We realised that some of the executives were not willing to take the risk, not for any risk of their own, but really just how the incentive structure set up within corporate." Nwadeyi discovered that knowing differently doesn't translate to acting differently when bonuses hang in the balance. The solution? Stop asking permission and build the innovation yourself. - On aligning incentives to unlock impossible markets: Working capital finance to informal retailers seemed impossible until Nwadeyi mapped the ecosystem. Wholesalers wanted more sales but couldn't offer credit. They did have transaction data. "Can we build a technology solution that interprets that data at scale to enable unique insight that traditional finance institutions don't have access to?" The result: finance the stock purchase to the wholesaler, the SME repays over 14 days, everyone wins. One of their spaza shop clients recently scaled from one store to three and bought her first house for R1 million (~USD 57,400) cash. - On thinking in decades whilst executing in months: "You don't have to think in days. You have to think in decades." Purchase Pal (what Nwadeyi claims to be "the world's first FMCG-embedded funeral insurance") represents one piece of a five-year strategy spanning multiple financial services verticals. The long game enables patient execution whilst maintaining corporate relevance. "What's my exit point? What's my entry point? Am I wanting to build this alongside?" - On why research beats assumptions every time: A tearful interview during his MPhil research - a woman describing the humiliation of borrowing money to bury her mother whilst neighbours gossiped about her poverty - sparked the Purchase Pal concept. "What if we could unlock quote unquote, what I call, no cost insurance?" Years of ethnographic research revealed the margin structure in FMCG goods, the cost burden of traditional insurance intermediation, and the customer stickiness problem facing consumer goods manufacturers. Research made the impossible obvious. Notable moment: The pivot from consultant to operator: Walking through a Cape Flats township, Nwadeyi's co-founder encountered a spaza shop owner struggling for financing. "All I ever wanted to do is to feed myself, feed my family or feed my business." That human story, repeated across thousands of township retailers, shifted SAG from insight provider to solution builder. Traditional finance wouldn't touch these operators. Nwadeyi's team reportedly deployed over R100 million (~USD 5.7 million) and achieved 99.9% repayment rates. Image credit: SAG Ventures

    17/10/2025

    •
    37 min
  • The Epstein Files didn’t hide this hacker very well

    1 DAY AGO

    8

    The Epstein Files didn’t hide this hacker very well

    Supposedly redacted Jeffrey Epstein files can still reveal exactly who they’re talking about - especially when AI, LinkedIn, and a few biographical breadcrumbs do the heavy lifting. Sloppy redaction leads to explosive claims, and difficult reputational consequences for cybersecurity vendors, and we learn how trust - once cracked - can be almost impossible to fully restore. Elsewhere, the spotlight turns to insider threat in the age of AI, after a senior US cybersecurity official uploads sensitive government material into the public version of ChatGPT. Oops. All this, and much more, in episode 453 of Smashing Security with cybersecurity veteran Graham Cluley and special guest Tricia Howard. EPISODE LINKS: Notepad++ hijacked to serve malware in targeted attacks - Notepad++.Porn-quitting app caught leaking users’ sexual habits - 404 Media.MicroWorld Technologies’ eScan anti-virus update turned into a malware delivery system - Morphisec.Jmail.World.Informant told FBI that Jeffrey Epstein had a ‘personal hacker’ - Techcrunch.Confidential informant statement given to FBI - US Department of Justice.Post by Graham Cluley - LinkedIn.Trump’s acting cyber chief uploaded sensitive files into a public version of ChatGPT - Politico.We are Lady Parts - Channel 4.We are Lady Parts trailer - YouTube.“Bashir with a good beard” by We are Lady Parts - YouTube.“Voldermort under my headscarf” by We are Lady Parts - YouTube.Doctor Who: The Shakespeare Notebooks - Penguin.Smashing Security merchandise (t-shirts, mugs, stickers and stuff) SPONSORS: Passwork - a reliable secrets manager and password management solution.Meter - Network infrastructure for the enterprise. Get a free personalised demo.Vanta - Expand the scope of your security program with market-leading compliance automation… while saving time and money. Smashing Security listeners get $1000 off! SUPPORT THE SHOW: Tell your friends and colleagues about “Smashing Security”, and leave us a review on Apple Podcasts or Podchaser. Become a supporter! Join Smashing Security PLUS via Patreon or Apple Podcasts for ad-free episodes on our early-release feed! FOLLOW THE SHOW: Follow us on Bluesky or Mastodon, or on the Smashing Security subreddit, and visit our website for more episodes. THANKS: Theme tune: "Vinyl Memories" by Mikael Manvelyan. Assorted sound effects: AudioBlocks. Privacy & Opt-Out: https://redcircle.com/privacy

    1 day ago

    •
    37 min
  • #535: Encryption vs Hashing: What's the real difference?

    3 DAYS AGO

    9

    #535: Encryption vs Hashing: What's the real difference?

    Big thank you to DeleteMe for sponsoring this video. Use my link http://joindeleteme.com/Bombal to receive a 20% discount or use the QR Code in the video. In this interview, David Bombal sits down with Dr. Mike Pound (Computerphile) to clear up one of the biggest crypto misconceptions on the Internet: hashing is not encryption, and hash functions are not reversible. In this video you’ll learn what a hash function actually does (a deterministic, fixed-length, “random-looking” summary of data) and why the whole point is that you cannot take a hash and reconstruct the original file. Dr Mike explains the key properties of secure hashing, including the avalanche effect (tiny input change, massive output change), and why older algorithms like MD5 and SHA-1 became unsafe due to collisions. We also cover what “collisions” really mean, why they must exist in theory (the pigeonhole principle) and why they can appear sooner than expected (the birthday paradox). Then we tackle the YouTube-comments classic: rainbow tables. If hashes are one-way, how do attackers “crack” passwords? The answer: they don’t reverse hashes. They guess passwords, hash them forward, and match the results. Mike breaks down how rainbow tables speed this up with precomputed hashes, and why salting makes those precomputations far less effective by forcing attackers to redo work per user. Finally, we zoom out into modern cryptography: why SHA-2 is widely used today, why SHA-3 exists as a structurally different backup option, what length extension attacks are, and what quantum computing changes (and doesn’t change) for hashing and encryption. We also touch on how hashes power digital signatures, file integrity checks (like verifying an ISO download), and why AES dominates symmetric encryption. // Mike's SOCIAL // X: / _mikepound // YouTube Video REFERENCE // SHA: Secure Hashing Algorithm: • SHA: Secure Hashing Algorithm - Computerphile Birthday Paradox: • Hash Collisions & The Birthday Paradox - C... The Next Big SHA? SHA3 Sponge Function Explained: • The Next Big SHA? SHA3 Sponge Function Exp... // David's SOCIAL // Discord: discord.com/invite/usKSyzb Twitter: www.twitter.com/davidbombal Instagram: www.instagram.com/davidbombal LinkedIn: www.linkedin.com/in/davidbombal Facebook: www.facebook.com/davidbombal.co TikTok: tiktok.com/@davidbombal YouTube: / @davidbombal Spotify: open.spotify.com/show/3f6k6gE... SoundCloud: / davidbombal Apple Podcast: podcasts.apple.com/us/podcast... // MY STUFF // https://www.amazon.com/shop/davidbombal // SPONSORS // Interested in sponsoring my videos? Reach out to my team here: sponsors@davidbombal.com // MENU // 0:00 - Coming up 01:09 - DeleteMe sponsored segment 02:54 - Hashing is not Encryption // Encryption and Hashing explained 09:47 - Hash functions are irreversible 15:22 - How hashing works 17:23 - Why MD5 is bad 20:09 - Recommended hashing function 21:47 - Birthday paradox explained 23:39 - Rainbow table explained 29:44 - Salting explained 33:35 - Pigeon Hole principle explained 36:35 - SHA-2 is the answer 37:17 - SHA-3 vs SHA-2 40:42 - The effect of quantum computing 42:47 - Quick summary 43:52 - Sign-In with private key 45:21 - Avalanche effect explained 49:10 - Where to learn more about hash functions 50:27 - Conclusion Please note that links listed may be affiliate links and provide me with a small percentage/kickback should you use them to purchase any of the items listed or recommended. Thank you for supporting me and this channel! Disclaimer: This video is for educational purposes only. #cryptography #hashing #encryption

    3 days ago

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    51 min
  • Ep 81: Ex-OpenAI Researcher On Why He Left, His Honest AGI Timeline, & The Limits of Scaling RL

    29 JAN

    10

    Ep 81: Ex-OpenAI Researcher On Why He Left, His Honest AGI Timeline, & The Limits of Scaling RL

    This episode features Jerry Tworek, a key architect behind OpenAI's breakthrough reasoning models (o1, o3) and Codex, discussing the current state and future of AI. Jerry explores the real limits and promise of scaling pre-training and reinforcement learning, arguing that while these paradigms deliver predictable improvements, they're fundamentally constrained by data availability and struggle with generalization beyond their training objectives. He reveals his updated belief that continual learning—the ability for models to update themselves based on failure and work through problems autonomously—is necessary for AGI, as current models hit walls and become "hopeless" when stuck. Jerry discusses the convergence of major labs toward similar approaches driven by economic forces, the tension between exploration and exploitation in research, and why he left OpenAI to pursue new research directions. He offers candid insights on the competitive dynamics between labs, the focus required to win in specific domains like coding, what makes great AI researchers, and his surprisingly near-term predictions for robotics (2-3 years) while warning about the societal implications of widespread work automation that we're not adequately preparing for.   (0:00) Intro (1:26) Scaling Paradigms in AI (3:36) Challenges in Reinforcement Learning (11:48) AGI Timelines (18:36) Converging Labs (25:05) Jerry’s Departure from OpenAI (31:18) Pivotal Decisions in OpenAI’s Journey (35:06) Balancing Research and Product Development (38:42) The Future of AI Coding (41:33) Specialization vs. Generalization in AI (48:47) Hiring and Building Research Teams (55:21) Quickfire   With your co-hosts:  @jacobeffron  - Partner at Redpoint, Former PM Flatiron Health  @patrickachase  - Partner at Redpoint, Former ML Engineer LinkedIn  @ericabrescia  - Former COO Github, Founder Bitnami (acq’d by VMWare)  @jordan_segall  - Partner at Redpoint

    29 Jan

    •
    1h 3m

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