🧠 OpenAI founder speaks out on talks with Anthropic and internal conflicts

In a deposition related to the company’s November 2023 leadership shake-up, co-founder Ilya Sutskever shared new details around merger discussions with Anthropic and internal tensions at OpenAI.

🖱 A merger proposition: Sutskever said that following the removal of Sam Altman, OpenAI’s board approached Dario Amodei of Anthropic about a potential deal. According to Sutskever, Anthropic was initially “excited” by the possibility.
🖱 Internal memo: Sutskever recorded a memo accusing Altman of “a consistent pattern of lying, undermining his execs, and pitting his execs against one another.”
🖱 Strategic fork: The merger discussions apparently stalled as Anthropic opted to chart its own path rather than combine with OpenAI.
🖱 Showdown for control: The deposition portrays the unfolding power struggle, not just with external rivals, but internally over mission, safety, transparency and leadership style.

AI companies continue to scale rapidly, these revelations shine a light on the growing pains and governance risks behind the scenes particularly the tension between commercial drive, safety oversight and founder-control.

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💰 Amazon signs $38B deal to supply OpenAI with Nvidia-powered compute

Amazon Web Services (AWS) has struck a seven-year, $38 billion agreement to provide OpenAI with access to hundreds of thousands of Nvidia GPUs, one of the largest infrastructure deals in AI history.

🖱 The deal secures OpenAI long-term access to Nvidia’s high-end chips through AWS data centers, ensuring stable compute supply for training and inference at scale.
🖱 It marks a deeper strategic partnership between Amazon and OpenAI, strengthening AWS’s position in the cloud race against Microsoft Azure and Google Cloud.
🖱 Nvidia, though not a signatory, remains the biggest beneficiary as its GPUs continue to underpin nearly every large-scale AI deployment.
🖱 The agreement underscores both the scale of OpenAI’s compute demand and its growing dependency on AWS infrastructure.

The scramble for AI compute is accelerating, and Amazon’s deal with OpenAI signals a power shift, where control over infrastructure, not model innovation, is becoming the real currency of dominance in the AI era.

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🍏 Apple targets nearly $140B holiday quarter with new iOS and iPad lineup

Apple is gearing up for a record ~$140 billion holiday quarter, driven by fresh software updates and a wave of hardware refreshes, as the company approaches its 50th anniversary.

🖱 Software push: The rollout of iOS 26.1 is imminent, with iOS 26.2 already in early beta, signaling Apple’s continued focus on ecosystem upgrades.
🖱 Hardware refresh: The MacBook Air, iPad Air, and iPad mini are all getting OLED displays, marking a major leap in screen quality across Apple’s mid-range lineup.
🖱 Retail revamp: Updated in-store product displays and experiences will launch starting November 12, timed with the holiday shopping surge.
🖱 Revenue momentum: The company’s near-record projection reflects strong pricing power and resilient demand across its product ecosystem.

Apple’s $140 billion target highlights how the company’s real advantage lies not just in individual devices, but in its tightly integrated ecosystem that turns every update into a catalyst for growth.

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💼 Director pay in startups shows how risk scales faster than reward

Directors at startups valued between $25 million and $250 million see only modest pay growth as valuations climb but their equity stakes shrink dramatically.

🖱 A tenfold increase in valuation doesn’t bring a tenfold rise in salary; compensation grows only slightly as companies mature.
🖱 Stock grants in larger startups are about 75% smaller than those in smaller ones, reflecting lower dilution tolerance and more stable structures.
🖱 Equity in later-stage startups is generally more likely to be worth something, while early-stage shares can easily end up worthless.
🖱 The trade-off highlights how financial upside narrows as companies derisk and valuations soar.

The startup pay curve reveals a clear truth, the bigger the company, the smaller the gamble, but also the smaller the win.

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🤖 Ex-consultants are now training AI models to do their old jobs

Former McKinsey, Bain, and BCG consultants are being hired to train AI systems designed to replicate the work of junior consultants from research to client slide decks.

🖱 Around 150 ex-consultants are working on a project called Argentum, run by a data-labelling firm developing models that can perform entry-level consulting tasks.
🖱 The AI is being trained to structure problems, analyze data, and produce client-ready materials, the same outputs that typically occupy analysts and associates.
🖱 By using real consultants to label and refine data, the system aims to capture not just workflows but the reasoning patterns behind professional consulting work.
🖱 The move points to a future where consulting’s “junior labor layer” could be automated, cutting both costs and entry-level opportunities.

The consulting pyramid may be flattening not by design, but by code.

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🎲 Coinbase CEO’s word stunt exposes cracks in prediction markets

Coinbase CEO Brian Armstrong deliberately dropped a string of buzzwords, “Bitcoin, Ethereum, blockchain, staking, Web3” during the company’s earnings call after learning that $84,000 was wagered on whether he’d say them.

🖱 Armstrong acknowledged tracking the bets in real time, then said the words live, instantly determining the outcome of active prediction-market contracts.
🖱 The incident revealed how “mention markets,” where users bet on specific phrases in public events, can be easily manipulated when the subject knows the wager.
🖱 Platforms like Kalshi and Polymarket now face scrutiny over whether such bets qualify as legitimate prediction tools or border on market manipulation.
🖱 Coinbase’s otherwise strong earnings were overshadowed by the episode, raising governance and regulatory questions around CEO conduct.

Prediction markets promise transparency but when the speaker controls the outcome, the odds no longer mean anything.

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🚀 Google to launch solar-powered space data centers with TPUs by 2027

Google has unveiled Project Suncatcher, an ambitious plan to deploy data centers in orbit, powered entirely by solar energy and equipped with its proprietary TPU chips for AI processing.

🖱 The first two satellites, each carrying four TPUs, are scheduled for launch in early 2027 to test full operational stability in orbit.
🖱 At an altitude of 650 km, the satellites will continuously harvest solar power unaffected by weather, time of day, or seasons.
🖱 Vacuum-based cooling could reduce maintenance costs by up to 40%, a major efficiency gain over Earth-based data centers.
🖱 Google says its TPUs have passed radiation resistance tests, performing 15× above the mission’s minimum threshold a strong sign of hardware readiness.

While the hardware works, key challenges remain from data transmission latency to orbital maintenance. And with startups like Starcloud aiming to have a full space data center running by 2027, Google’s race to scale AI infrastructure beyond Earth is officially on.

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⚖️ Amazon sues Perplexity over AI agent that shops on its own

Amazon has filed a lawsuit against Perplexity AI, claiming the startup’s browser agent “Comet” made unauthorized purchases on Amazon’s marketplace violating the platform’s terms of service and U.S. computer-fraud laws.

🖱 According to Amazon, Comet allows users to buy items without disclosing that an AI, not a person, is completing the transaction.
🖱 The case was filed in federal court in San Francisco and demands Perplexity immediately halt all such automated purchases.
🖱 Amazon argues the practice undermines marketplace integrity and poses risks for fraud and misrepresentation.
🖱 Perplexity, known for its fast-growing AI search and agent tools, has not yet issued a detailed public response.

The dispute highlights a growing legal gray zone: how far autonomous AI agents can go in acting for humans in online commerce. With Amazon defending platform control and Perplexity pushing agentic innovation, this could set a landmark precedent for AI behavior in digital marketplaces.

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💬 Reddit pitches itself as the key to brand visibility in AI search results

A leaked Reddit presentation reviewed by Adweek shows the platform courting advertisers with a new promise better exposure inside AI-powered search and answer systems.

🖱 The deck claims Reddit ads can help brands appear more often in AI summaries by surfacing their content in high-engagement community threads.
🖱 It suggests reviving old posts, partnering with Discord groups, or hiring third parties to seed new discussions that AI models might later index.
🖱 Ad buyers confirmed growing interest in this tactic, treating Reddit less as a social network and more as a gateway to AI visibility.
🖱 The strategy reflects a broader marketing shift from traditional SEO toward optimizing for generative-AI outputs.

As AI systems become the new discovery layer of the internet, Reddit’s trove of authentic discussions could turn into prime real estate for brands chasing algorithmic attention but at the cost of blurring the line between genuine community dialogue and paid influence.

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🧠 Sam Altman’s Merge Labs aims to connect human brains to AI, no surgery required

OpenAI founder Sam Altman is backing Merge Labs, a new brain-computer interface startup that wants to link human thought directly to machines but without the skull implants used by Elon Musk’s Neuralink.

🖱 Merge’s researchers are exploring a non-invasive BCI that could use genetic modifications and ultrasound instead of physical electrodes.
🖱 The idea: modify neurons so they produce proteins that react to ultrasound, allowing a scanning cap to read brain activity and send it to a computer.
🖱 This method could dramatically speed up adoption by removing the need for surgery, though safety testing remains a major hurdle.
🖱 Beyond medical applications like restoring vision, Altman envisions everyday integrations with AI systems from thought-based interfaces to real-time digital communication.

If Merge succeeds, brain-computer links could shift from sci-fi to mass market but the ethical questions will only grow louder than the ultrasound waves powering them.

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🧠 Apple turns to Google’s 1.2T-parameter Gemini model to reinvent Siri

Apple is reportedly finalizing a nearly $1 billion-per-year deal with Google to power the next generation of Siri using the Gemini 1.2 trillion-parameter model, one of the largest AI systems ever deployed in consumer devices.

🖱 The move marks Apple’s biggest AI partnership yet, signaling a shift from building in-house models to licensing Google’s foundation AI for deep reasoning and contextual understanding.
🖱 Gemini would enable Siri to handle complex, multi-step requests and maintain long-term memory across Apple’s ecosystem, from iPhone to Vision Pro.
🖱 The integration could make Siri competitive again after years of lagging behind ChatGPT, Claude, and Alexa in conversational depth.
🖱 Still, the partnership raises questions about privacy, data sharing, and Apple’s dependence on a direct rival’s infrastructure.

Apple’s smartest assistant yet may be powered by Google’s brain, a rare alignment that blurs the line between Silicon Valley’s fiercest competitors.

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🚀 B2B GTM in 2025 was chaos 2026 will be scale or die

A new report from Kyle Poyar’s Growth Unhinged surveyed 195 SaaS and AI startup leaders ($1–10M ARR) and found one thing clear: 2025 was the year of GTM experimentation. 2026 will be the year of ruthless focus.

🖱 23% of startups relied on inbound, 19% on outbound, and 18% on account-based GTM — but effectiveness depended entirely on deal size. Under $5K? Product-led + founder-led outbound. Over $25K? Personalized, account-based outreach wins.
🖱 Startups now juggle an average of 10+ marketing channels, spreading teams thin and burning cash. The highest ROI came from LinkedIn (66%), SEO (53%), and warm outbound (48%), while TikTok, PR, and Reddit barely registered.
🖱 The best-performing playbooks leaned on intent-based outbound, AI-assisted search, and closed events even small private dinners that could close six-figure deals.
🖱 91% of companies used ChatGPT, but over half saw no ROI. Tools like Clay, HubSpot, and Lovable are emerging as GTM automation favorites for 2026.

Next year’s mantra: cut the noise, double down on 2–3 high-intent channels, and apply AI only where it multiplies returns not where it adds complexity.

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💰 AI startups just broke every funding record in venture history

According to PitchBook, investors are pouring more capital into AI startups than in any previous tech boom from crypto to social media to mobile combined.

🖱 In the first half of 2025 alone, AI companies raised $104 billion in the U.S., capturing nearly two-thirds of all VC funding.
🖱 Globally, 57.9% of venture dollars went to AI and machine-learning startups, the highest concentration ever recorded.
🖱 Over the past three years, investors have funneled $330 billion into roughly 26,000 AI ventures, betting that the next trillion-dollar outcome will emerge here.
🖱 Yet many of these startups still lack clear revenue models or defensible moats, raising fears of a “post-AI bubble” shakeout.

If this momentum continues, 2025 will be remembered not just as the peak of the AI hype cycle, but as the year capital itself became artificially intelligent.

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🚗 Tesla shareholders back Elon Musk’s record $1 trillion pay plan

Tesla investors have approved a massive compensation package for CEO Elon Musk potentially worth up to $1 trillion in stock if the company hits a series of ambitious growth milestones.

🖱 Over 75% of voting shareholders supported the new plan, which ties Musk’s payout entirely to Tesla’s performance.
🖱 The package spans 12 tranches linked to operational goals, adjusted profits, and a market-cap target of $8.5 trillion, nearly six times Tesla’s current value.
🖱 Musk receives no base salary or cash bonus; all rewards depend on reaching these benchmarks.
🖱 The approval follows a court decision voiding his earlier $56 billion plan over governance concerns.

The vote marks one of the boldest compensation gambles in corporate history, a bet that Tesla’s valuation can soar to unprecedented heights. If Musk delivers, shareholders gain enormously; if not, the package will stand as a cautionary tale of ambition outpacing reality.

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🔥 Sam Altman snaps at investor Brad Gerstner over OpenAI spending question

Things got tense on the BG2 podcast when Altimeter’s Brad Gerstner pressed Sam Altman on how OpenAI could justify $1.4 trillion in spending commitments with “just” $13 billion in annual revenue all while Microsoft CEO Satya Nadella sat beside him.

🖱 Gerstner asked how OpenAI could afford such massive compute and infrastructure bets relative to its earnings.
🖱 Altman sharply pushed back: “We’re doing well more revenue than that… Brad, if you want to sell your shares, I’ll find you a buyer.”
🖱 He went on to defend OpenAI’s aggressive growth plan saying the company is betting on steep revenue growth, new consumer devices, and AI systems that “automate science.”
🖱 Nadella stepped in to cool the moment, noting that OpenAI consistently exceeds its forecasts, though the tension visibly lingered.

Gerstner later downplayed the clash on X, writing that they “laughed about it afterwards.” But the exchange revealed real strain between investor caution and founder conviction and raised a sharper question: is this confidence, frustration, or a sign of how high the stakes have become for OpenAI’s next phase?

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⚙️ Google’s new Ironwood chip takes aim at Nvidia’s AI dominance

Google has unveiled Ironwood, a powerful new tensor processor built specifically for training and running massive AI models and it’s already being compared to Nvidia’s top-tier chips. Delivering 4.6 petaflops of compute, Ironwood rivals the Nvidia B200 and GB200 in raw performance.

🖱 Ironwood is purpose-built for large-scale model workloads, optimized for Google Cloud’s AI infrastructure to accelerate both training and inference.
🖱 Anthropic has reportedly ordered 1 million Ironwood chips to power future versions of Claude marking one of the largest single AI hardware deals to date.
🖱 Sales will begin in the coming weeks, positioning Google as a direct supplier of cutting-edge silicon to major AI labs.
🖱 The launch underscores Google’s strategy to compete not just in AI software, but in the entire compute stack, from chips to models to cloud deployment.

With Ironwood, Google isn’t just catching up to Nvidia,it’s rewriting the balance of power in the global AI hardware race.

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📊 Crypto Venture Weekly: November 3–7, 2025

$630M was raised across 16 projects this week, led by Ripple’s $500M strategic round at a $40B valuation. At the same time, BitMine, Evernorth, Strategy, Future Holdings, and Strive announced $564M in new digital asset treasury allocations across BTC, ETH, and XRP.

Here’s what the top 8 are building 👇

🖱 Ripple ($500M, Citadel, Fortress, Pantera, Brevan Howard, Marshall Wace)
Enterprise blockchain for cross-border payments, expanding institutional liquidity and settlement.

🖱 fomo ($17M, Benchmark, Coinbase Ventures, Archetype)
Consumer-focused crypto trading app simplifying onchain investing.

🖱 Donut Labs ($15M, Hack VC, Bitkraft, Inception, Makers Fund)
Agentic crypto browser enabling autonomous, AI-driven Web3 experiences.

🖱 Liquid ($7.6M, Paradigm, General Catalyst)
Perpetuals DEX aggregator improving price discovery and execution across trading venues.

🖱 Arx Research ($6.1M, Castle Island, 1kx, Placeholder)
Building handheld point-of-sale devices for everyday digital asset payments.

🖱 Harmonic ($6M, Paradigm, Solana ecosystem backers)
Open block-building system optimizing validator revenue and throughput on Solana.

🖱 Sprinter ($5.2M, Robot Ventures, Uniswap, A.Capital)
Crosschain “solving-as-a-service” infrastructure for interoperability and computation.

🖱 Zynk ($5M, Hivemind, Coinbase, Alliance DAO)
Settlement infrastructure enabling instant global payments with onchain finality.

Investor attention this week centered on infrastructure, AI convergence, and real-world payments, with Ripple’s expansion marking another step toward institutional blockchain adoption and decentralized finance at scale.

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💰 Meta’s billion-dollar problem: profits from scam ads

Meta is quietly earning a fortune from fraudulent advertising, according to internal documents revealed by Reuters. Roughly 10% of Meta’s 2024 revenue; about $16 billion, came from scam or banned ads, flooding its platforms with billions of deceptive promotions each day.

🖱 Meta’s systems displayed up to 15 billion “high-risk” scam ads daily, often easier to post than on Google.
🖱 Even repeat offenders weren’t removed: some advertisers amassed 500+ violations and stayed active because they spent heavily.
🖱 A so-called “penalty bid” system charged suspected scammers higher rates, so Meta still profited from them instead of banning them.
🖱 Regulators are circling: the SEC and UK authorities are probing Meta after reports that over half of payment-fraud losses trace back to its platforms.

Meta aims to shrink scam-ad revenue to 6% by 2026 but cutting that stream could hurt profits in the short term.

In chasing ad dollars, Meta may have optimized for growth at the expense of integrity and regulators are starting to notice.

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☀️ Google to launch solar-powered space data centers with TPUs by 2027

Just a day after the first Nvidia H100 reached orbit, Google has announced Project Suncatcher, an ambitious plan to deploy space-based data centers powered entirely by solar energy.

🖱 Each orbital unit will operate at 650 km altitude, collecting uninterrupted sunlight unaffected by weather, time of day, or seasons.
🖱 The vacuum environment enables natural cooling, potentially cutting maintenance costs by up to 40%.
🖱 Google’s custom TPUs have passed radiation-resistance tests, performing 15× better than the mission’s minimum standard.
🖱 In early 2027, Google plans to launch two satellites carrying four TPUs each to validate full system performance before scaling further.

Competitors are racing too, startup Starcloud claims it will have a complete orbital data center operational by the same year.

If Suncatcher succeeds, it could redefine cloud infrastructure, where compute power finally leaves Earth’s atmosphere.

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🚐 Waymo hits the gas: robotaxis roll into Detroit, Vegas & San Diego

Alphabet-owned Waymo is expanding its driverless taxi network into three new U.S. cities, Detroit, Las Vegas, and San Diego,marking its fastest rollout yet. The move comes as Waymo targets 1 million rides per week by 2026, up from roughly 250,000 earlier this year.

🖱 Each city serves a strategic testbed: Detroit’s snow, Las Vegas’s traffic, and San Diego’s suburban sprawl push the system’s weather and mapping limits.
🖱 The fleet will include both Jaguar I-Pace EVs and Zeekr RT prototypes, blending legacy auto hardware with Waymo’s in-house AI stack.
🖱 Rollout starts with mapping and safety-driver phases before public service launches, following Waymo’s gradual expansion model.
🖱 The company now operates or tests in eight major metros, outpacing rivals like Cruise and Zoox after recent regulatory and safety setbacks in the industry.

Waymo’s expansion signals a shift from pilot projects to scaled commercial ops and a bet that diversified geography, not just tech leadership, will define who owns the future of autonomous mobility.

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💥 The big (fake?) AI short: how media sold Burry’s phantom bet

Michael Burry didn’t actually short Nvidia or Palantir for “$900 million” but that didn’t stop headlines from saying he did. His latest 13F filing became clickbait gold for financial media hungry for an AI bubble narrative.

🖱 Outlets from FT to Bloomberg framed Burry’s positions as a massive anti-AI bet, claiming Scion Asset Management shorted 80% of its portfolio.
🖱 In reality, 13F forms only show long positions, we can’t see whether he hedged, shorted, or offset those puts elsewhere.
🖱 The filings don’t reveal strike prices or expirations, meaning the actual value of the “$900M” put exposure could range from millions to nearly zero.
🖱 The ambiguity made it perfect clickbait: “Burry vs. the AI boom” is a better story than “data unclear.”

By turning nuance into narrative, the media converted paperwork into panic, proof that in the attention economy, the scariest number wins.

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