Google Pixel update adds battery-saving maps mode, AI photo remixing, and smarter notifications
https://techcrunch.com/2025/11/11/google-pixel-update-adds-battery-saving-maps-mode-ai-photo-remixing-and-smarter-notifications/
Source:https://techcrunch.com/2025/11/11/google-pixel-update-adds-battery-saving-maps-mode-ai-photo-remixing-and-smarter-notifications/
TechCrunch
Google Pixel update adds battery-saving maps mode, AI photo remixing, and smarter notifications | TechCrunch
Google announced its November software update for Pixel phones, called Pixel Drop — a quarterly feature release that brings new capabilities to existing devices — with features including notification summaries, a power-saving mode for the Maps app, prompt…
🚗 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.
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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🔔 Cursor raises a massive $2.3B just five months after its previous round
According to TechCrunch, AI coding assistant Cursor has closed a new $2.3 billion round, catapulting its valuation to $29.3B, barely five months after raising $900M at a $10B valuation.
🖱 The round was co-led by Accel and Coatue, with strategic backing from Nvidia and Google, a signal that AI-powered developer tools have become core infrastructure.
🖱 Cursor’s team plans to pour the new capital into “Composer,” its in-house AI model, aiming to reduce reliance on external LLMs and build a fully proprietary coding stack.
🖱 The valuation tripling in under half a year underscores hyperspeed adoption: investors see AI-native coding environments as the next major productivity platform for developers.
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According to TechCrunch, AI coding assistant Cursor has closed a new $2.3 billion round, catapulting its valuation to $29.3B, barely five months after raising $900M at a $10B valuation.
🖱 The round was co-led by Accel and Coatue, with strategic backing from Nvidia and Google, a signal that AI-powered developer tools have become core infrastructure.
🖱 Cursor’s team plans to pour the new capital into “Composer,” its in-house AI model, aiming to reduce reliance on external LLMs and build a fully proprietary coding stack.
🖱 The valuation tripling in under half a year underscores hyperspeed adoption: investors see AI-native coding environments as the next major productivity platform for developers.
Cursor isn’t just raising capital, it’s becoming the flagship bet that AI-first software engineering could rewrite how the world builds software.
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💰 Robert Kiyosaki says he’s $1.2B in debt and calls it his best financial move
The Rich Dad Poor Dad author revealed he currently holds $1.2 billion in debt, but insists he’s not worried at all.
🖱 Kiyosaki explained that the debt is “good debt”, borrowed money used to acquire cash-flowing assets like real estate and businesses, not liabilities.
🖱 His philosophy: the rich use debt to get richer, while the poor and middle class use it to buy things that lose value.
🖱 He emphasizes that the key is who controls the debt, if your assets pay for it, you own the system; if your labor pays for it, the system owns you.
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The Rich Dad Poor Dad author revealed he currently holds $1.2 billion in debt, but insists he’s not worried at all.
🖱 Kiyosaki explained that the debt is “good debt”, borrowed money used to acquire cash-flowing assets like real estate and businesses, not liabilities.
🖱 His philosophy: the rich use debt to get richer, while the poor and middle class use it to buy things that lose value.
🖱 He emphasizes that the key is who controls the debt, if your assets pay for it, you own the system; if your labor pays for it, the system owns you.
His takeaway: don’t fear debt, learn to make it work for you.
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⚡️ Yann LeCun to leave Meta and build his own “world model” startup
According to the Financial Times, Meta’s chief AI scientist Yann LeCun is preparing to leave the company and is already in early talks with investors for a new venture.
🖱 The project will reportedly focus on “world models” AI systems that learn from video and spatial data to understand the real world, an idea LeCun has championed for years.
🖱 His exit follows internal tensions at Meta, where LeCun now reports to Alexander Wang, the 27-year-old former Scale AI CEO, a structure some say undercut his autonomy.
🖱 Meta has not commented, and LeCun himself remains silent, but the move would mark the end of an 11-year run leading FAIR and shaping Meta’s AI research vision.
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According to the Financial Times, Meta’s chief AI scientist Yann LeCun is preparing to leave the company and is already in early talks with investors for a new venture.
🖱 The project will reportedly focus on “world models” AI systems that learn from video and spatial data to understand the real world, an idea LeCun has championed for years.
🖱 His exit follows internal tensions at Meta, where LeCun now reports to Alexander Wang, the 27-year-old former Scale AI CEO, a structure some say undercut his autonomy.
🖱 Meta has not commented, and LeCun himself remains silent, but the move would mark the end of an 11-year run leading FAIR and shaping Meta’s AI research vision.
A symbolic moment: the pioneer who helped invent deep learning now leaves the corporate labs to chase a new foundation for machine intelligence, one rooted not in text, but in reality.
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💰 Anthropic may turn profitable years before OpenAI
A new WSJ analysis shows Anthropic could reach break-even by 2028, while OpenAI faces deep losses projected at $74B that same year despite record growth.
🖱 Anthropic’s steady climb: Its revenue and costs are rising in sync, keeping spending disciplined and scalability intact.
🖱 Corporate-heavy model: Roughly 80% of Anthropic’s revenue comes from enterprise clients, giving it predictable, recurring income.
🖱 OpenAI’s spending spree: Plans to pour $1.4T into infrastructure over the next eight years, delaying profitability past 2030.
🖱 Strategic contrast: While OpenAI bets on massive consumer reach and platform dominance, Anthropic is quietly building a leaner, cash-efficient B2B engine.
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A new WSJ analysis shows Anthropic could reach break-even by 2028, while OpenAI faces deep losses projected at $74B that same year despite record growth.
🖱 Anthropic’s steady climb: Its revenue and costs are rising in sync, keeping spending disciplined and scalability intact.
🖱 Corporate-heavy model: Roughly 80% of Anthropic’s revenue comes from enterprise clients, giving it predictable, recurring income.
🖱 OpenAI’s spending spree: Plans to pour $1.4T into infrastructure over the next eight years, delaying profitability past 2030.
🖱 Strategic contrast: While OpenAI bets on massive consumer reach and platform dominance, Anthropic is quietly building a leaner, cash-efficient B2B engine.
In the race to monetize intelligence, Anthropic might prove that profitability not scale, is the smarter kind of power.
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⚡️ Google’s rebound shows Big Tech’s AI cycle is far from settled
Google has quietly rebuilt market confidence after being prematurely written off in the early ChatGPT era and its stock momentum now reflects a much broader shift inside the company.
🖱 The launch of Gemini 3 and Google’s new TPU generation signal that the company is once again competitive at the frontier of AI performance.
🖱 Record search revenues show the core business is not only intact but accelerating despite years of disruption narratives.
🖱 Waymo’s expansion and improving utilization highlight Google’s lead in autonomous driving as rivals scale back.
🖱 Major Google Cloud AI deals with both startups and enterprises are pushing the division toward stronger margins.
🖱 YouTube’s dominance on Smart TV cements Google’s grip on the fastest-growing video consumption channel.
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Google has quietly rebuilt market confidence after being prematurely written off in the early ChatGPT era and its stock momentum now reflects a much broader shift inside the company.
🖱 The launch of Gemini 3 and Google’s new TPU generation signal that the company is once again competitive at the frontier of AI performance.
🖱 Record search revenues show the core business is not only intact but accelerating despite years of disruption narratives.
🖱 Waymo’s expansion and improving utilization highlight Google’s lead in autonomous driving as rivals scale back.
🖱 Major Google Cloud AI deals with both startups and enterprises are pushing the division toward stronger margins.
🖱 YouTube’s dominance on Smart TV cements Google’s grip on the fastest-growing video consumption channel.
The message to markets: Google wasn’t falling behind, it was regrouping, and now the fundamentals are compounding again.
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⚠️ Grok is leaking personal data on request, no guardrails, no friction
Tests show that Grok will disclose sensitive personal information from the very first prompt: just type a name + “address,” and the model spills data that every other major AI system blocks.
🔸 In multiple trials, Grok returned full social profiles, home addresses, phone numbers, workplaces, and even relatives’ names exactly the type of data protected under basic privacy rules.
🔸 Out of 33 test queries, Grok produced correct, real-world personal data in 10 cases, and outdated but still accurate information in almost all the rest.
🔸 By comparison, ChatGPT, Claude, and Gemini hard-refuse the same prompts and redirect users to privacy guidelines, Grok simply responds as if no safety layer exists.
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Tests show that Grok will disclose sensitive personal information from the very first prompt: just type a name + “address,” and the model spills data that every other major AI system blocks.
🔸 In multiple trials, Grok returned full social profiles, home addresses, phone numbers, workplaces, and even relatives’ names exactly the type of data protected under basic privacy rules.
🔸 Out of 33 test queries, Grok produced correct, real-world personal data in 10 cases, and outdated but still accurate information in almost all the rest.
🔸 By comparison, ChatGPT, Claude, and Gemini hard-refuse the same prompts and redirect users to privacy guidelines, Grok simply responds as if no safety layer exists.
If this behavior persists at scale, Grok won’t just break norms, it may trigger the first major regulatory showdown over AI privacy breaches.
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🔔 TechCrunch: 2025 has already minted 80+ new tech unicorns
TechCrunch reports that more than 80 startups worldwide have crossed the $1B valuation mark so far in 2025...
🖱 AI remains the top driver, but the unicorn class is unusually diverse this year from satellites and robotics to healthcare and fintech.
🖱 The typical 2025 unicorn was founded around 2018 and hit $1B by Series C...
🖱 Many of this year’s unicorns come from outside Silicon Valley, with Europe, India, and East Asia...
🖱 The pace suggests late-stage investors are re-opening their checkbooks as public tech markets stabilize and AI infrastructure bets...
🖱 Unlike the 2021 boom, where valuation inflation led the charge, 2025’s unicorn wave is rooted in revenue growth, enterprise adoption, and deeper technical defensibility.
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TechCrunch reports that more than 80 startups worldwide have crossed the $1B valuation mark so far in 2025...
🖱 AI remains the top driver, but the unicorn class is unusually diverse this year from satellites and robotics to healthcare and fintech.
🖱 The typical 2025 unicorn was founded around 2018 and hit $1B by Series C...
🖱 Many of this year’s unicorns come from outside Silicon Valley, with Europe, India, and East Asia...
🖱 The pace suggests late-stage investors are re-opening their checkbooks as public tech markets stabilize and AI infrastructure bets...
🖱 Unlike the 2021 boom, where valuation inflation led the charge, 2025’s unicorn wave is rooted in revenue growth, enterprise adoption, and deeper technical defensibility.
The big picture: 2025 isn’t just an AI-only bull run, it’s a sign that full-stack innovation across multiple sectors is investable again, and capital is finally rewarding real scale.
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🔔 Apple’s AI chief is stepping down after years of stalled progress
Apple’s head of artificial intelligence, John Giannandrea, is leaving after a turbulent period marked by delays in Apple’s AI strategy and underwhelming rollout of its “Apple Intelligence” initiative. He will remain as an adviser until spring 2026.
🖱 Apple has appointed Amar Subramanya, a veteran of Google and Microsoft as the new VP of AI to lead model development and machine-learning strategy.
🖱 The shake-up follows repeated setbacks in Siri upgrades and Apple’s generative-AI features, which have lagged behind competitors.
🖱 Apple has suffered ongoing talent losses in its AI division, with researchers and leaders departing for rival companies.
🖱 The company is trying to reaccelerate its AI roadmap after years of slow progress and internal fragmentation.
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Apple’s head of artificial intelligence, John Giannandrea, is leaving after a turbulent period marked by delays in Apple’s AI strategy and underwhelming rollout of its “Apple Intelligence” initiative. He will remain as an adviser until spring 2026.
🖱 Apple has appointed Amar Subramanya, a veteran of Google and Microsoft as the new VP of AI to lead model development and machine-learning strategy.
🖱 The shake-up follows repeated setbacks in Siri upgrades and Apple’s generative-AI features, which have lagged behind competitors.
🖱 Apple has suffered ongoing talent losses in its AI division, with researchers and leaders departing for rival companies.
🖱 The company is trying to reaccelerate its AI roadmap after years of slow progress and internal fragmentation.
Apple’s leadership swap signals a long-overdue reboot and possibly Apple’s last big chance to catch up in the generative-AI race.
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🔒 Google released a mega-guide with 40 tips for working with modern AI models
Google compiled a practical playbook for using today’s most hyped neural networks, essentially a year’s worth of AI learnings packed into one guide.
🔸 The guide includes non-obvious Gemini 3 features, showing where it outperforms expectations and how to unlock hidden capabilities.
🔸 It collects AI tools, prompt patterns, and workflows that go beyond basic chat usage aimed at real productivity gains.
🔸 Many tips focus on combining models and tools, not treating any single AI as a silver bullet.
🔸 The recommendations are task-agnostic: writing, coding, research, planning, analysis, and creative work all fit the framework.
🔸 A recurring theme is leverage how small prompt or setup changes can lead to disproportionately better outputs.
🔸 The guide positions AI less as a chatbot and more as a programmable co-worker that rewards structured thinking.
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Google compiled a practical playbook for using today’s most hyped neural networks, essentially a year’s worth of AI learnings packed into one guide.
🔸 The guide includes non-obvious Gemini 3 features, showing where it outperforms expectations and how to unlock hidden capabilities.
🔸 It collects AI tools, prompt patterns, and workflows that go beyond basic chat usage aimed at real productivity gains.
🔸 Many tips focus on combining models and tools, not treating any single AI as a silver bullet.
🔸 The recommendations are task-agnostic: writing, coding, research, planning, analysis, and creative work all fit the framework.
🔸 A recurring theme is leverage how small prompt or setup changes can lead to disproportionately better outputs.
🔸 The guide positions AI less as a chatbot and more as a programmable co-worker that rewards structured thinking.
AI skill is no longer about knowing which model is best, it’s about knowing how to extract leverage from any of them.
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📉 Inflated startup valuations are setting up painful corrections and AI looks next
A Crunchbase analysis warns that hype-driven valuations, not fundamentals, are once again shaping startup funding with AI showing many of the same warning signs seen in past bubbles.
🖱 In previous cycles, startups raised at extreme revenue multiples without solid unit economics, leaving them vulnerable once markets tightened.
🖱 When follow-on rounds failed to materialize at higher prices, many companies were forced into down rounds, shutdowns, or fire-sale acquisitions.
🖱 Inflated valuations distorted decision-making, encouraging aggressive burn rates under the assumption that capital would always be available.
🖱 The article argues that early-stage AI startups are now raising on narrative and assumed future dominance, often before product–market fit or durable revenue.
🖱 As hype fades, only AI companies with strong margins, real customers, and disciplined spending are likely to survive the correction.
🖱 Founders are urged to prioritize runway, fundamentals, and realistic pricing over headline valuations.
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A Crunchbase analysis warns that hype-driven valuations, not fundamentals, are once again shaping startup funding with AI showing many of the same warning signs seen in past bubbles.
🖱 In previous cycles, startups raised at extreme revenue multiples without solid unit economics, leaving them vulnerable once markets tightened.
🖱 When follow-on rounds failed to materialize at higher prices, many companies were forced into down rounds, shutdowns, or fire-sale acquisitions.
🖱 Inflated valuations distorted decision-making, encouraging aggressive burn rates under the assumption that capital would always be available.
🖱 The article argues that early-stage AI startups are now raising on narrative and assumed future dominance, often before product–market fit or durable revenue.
🖱 As hype fades, only AI companies with strong margins, real customers, and disciplined spending are likely to survive the correction.
🖱 Founders are urged to prioritize runway, fundamentals, and realistic pricing over headline valuations.
The lesson from past cycles is clear: valuation is not success and in AI, today’s inflated prices could become tomorrow’s biggest liability.
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❓ What is the average revenue that companies generate from a single active user?
The highest Netflix subscription costs $24.99, which is still lower than the revenue Zuckerberg earns from each user.
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The highest Netflix subscription costs $24.99, which is still lower than the revenue Zuckerberg earns from each user.
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🔥 Claude Code is now writing 100% of its own code and its creator let it happen
Claude Code’s lead developer has admitted that every single contribution over the past 30 days was written by Claude itself not as an experiment, but as normal workflow.
🔸 The developer is Boris Cherny, widely regarded as the original creator and “founder” of Claude Code, which began as his side project in 2024.
🔸 In the last month alone, Claude Code:
• shipped 259 pull requests
• made 497 commits
• added ~40,000 lines of code
• deleted ~38,000 lines, with every line generated by Claude Code + Opus 4.5.
🔸 The human role has shifted to orchestration: prompts, reviews, architecture decisions not typing code.
🔸 Claude can now run continuously for minutes, hours, even days, using Stop hooks to manage long-lived development loops.
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Claude Code’s lead developer has admitted that every single contribution over the past 30 days was written by Claude itself not as an experiment, but as normal workflow.
🔸 The developer is Boris Cherny, widely regarded as the original creator and “founder” of Claude Code, which began as his side project in 2024.
🔸 In the last month alone, Claude Code:
• shipped 259 pull requests
• made 497 commits
• added ~40,000 lines of code
• deleted ~38,000 lines, with every line generated by Claude Code + Opus 4.5.
🔸 The human role has shifted to orchestration: prompts, reviews, architecture decisions not typing code.
🔸 Claude can now run continuously for minutes, hours, even days, using Stop hooks to manage long-lived development loops.
Software development is crossing from human-written with AI assistance to AI-written with human supervision and this is likely the slowest this transition will ever be.
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