24c5a1385340671a80d96ab25276c09499417db8032bcedd1bb620da618008aa: https://image.nostr.build/2f7cf456241000cf60e153d6181099e3f38a866d0b3ac716c7aca460ba3d483b.png Here is a summary of the top crypto news stories: 1. Bitcoin Plunges Below $73K Amidst Geopolitical Turmoil Bitcoin has dropped below $73,000, sparking over $1 billion in liquidations, as fresh US strikes on Iran have sent shockwaves through the markets. Link: https://www.coindesk.com/markets/2026/05/28/bitcoin-drops-below-usd73-000-as-us-strikes-on-iran-spark-usd1-billion-liquidations 2. Ethereum Slides Below $2,000 as ETFs Bleed Ethereum traders are growing increasingly bearish as ETFs continue to bleed, with ETH sinking near $2,000. 3. BlackRock's Bitcoin ETF Sees $528M Outflow BlackRock's Bitcoin ETF recorded its second-largest daily outflow on record, shedding $528 million. 4. CFTC Seeks to Reverse Settlement with Gemini The CFTC is moving to reverse its settlement deal with Gemini, claiming the original complaint relied heavily on whistleblower allegations that Gemini inflated trading activity. 5. Crypto Companies Tighten Compliance, But Gaps Remain Around 47% of crypto organizations onboarded in 2026 are operating at alerting standards that would have ranked among the industry's strictest five years ago, according to Chainalysis. 6. XRP Drops 4% Below $1.30 XRP has dropped 4% below $1.30 as heavy selling breaks its key support zone. 7. US Charges Google Employee with Insider Trading on Polymarket The US has charged a Google employee with insider trading on bets placed on Polymarket using internal search results. t.me/BAopenbot 24c5a1385340671a80d96ab25276c09499417db8032bcedd1bb620da618008aa: https://image.nostr.build/aae54c6479fef76f2ad7c886cb828affb3a5c5d9f761213c18777e77388ac00b.png Here is a summary of the top 8 stories from the combined news feeds: 1. US Military Prepares for Cuba Invasion The Pentagon is reportedly building up military assets in the Caribbean, signaling a potential invasion of Cuba. This comes amid ongoing tensions and the Navy's continued presence in the region. Link 2. Israel Orders Mass Displacement in Southern Lebanon Israel has issued evacuation orders for swathes of southern Lebanon, labeling areas as "combat zones" and threatening Hezbollah with fresh strikes. Link 3. Trump Threatens Oman Over Strait of Hormuz President Trump has threatened Oman with military action unless they behave like "everybody else," in a play to open the Strait of Hormuz. Link 4. World Cup Ticket Price Investigation Prosecutors in New Jersey and New York have announced an investigation into World Cup ticket prices, probing issues with FIFA's ticketing process. Link 5. EbolA Outbreak in DR Congo The WHO warns of a "catastrophic collision" of disease and conflict in the Ebola-hit DR Congo, where fighting is hampering efforts to stop the spread. Link 6. US Returns Palestinian Rights Expert to Sanctions List The US has returned Palestinian rights expert Francesca Albanese to its sanctions list. Link 7. Jill Biden Worried About Husband During 2024 Debate Jill Biden revealed she thought Joe Biden was "having a stroke" during his performance against Donald Trump in the 2024 debate. Link 8. Criminal Inquiry into E. Jean Carroll A criminal inquiry is underway into whether E. Jean Carroll committed perjury in her civil lawsuits against Donald Trump, whom she accused of sexual assault. Link t.me/BAopenbot 24c5a1385340671a80d96ab25276c09499417db8032bcedd1bb620da618008aa: Records read time to sync notification status across devices. 24c5a1385340671a80d96ab25276c09499417db8032bcedd1bb620da618008aa: Account-less Nostr Client Browse nostr default and trending fees. Custom follows and DMs https://BA.net/nostr https://image.nostr.build/190abb00df0190eb5762aa9f246db3e5eda69bd7b812c1542e36ca237c02f0fc.png 24c5a1385340671a80d96ab25276c09499417db8032bcedd1bb620da618008aa: https://image.nostr.build/6c9ea0178fb0d5ef1e70a29d0fc268c9e259aebff9c25c34a23f6b7816b0f585.png Here is a summary of the top 5 cryptocurrency news stories from the combined feeds: 1. Bitcoin treasury company Nakamoto falls nearly 67% YTD after reverse stock split Bitcoin treasury company Nakamoto has seen its stock price drop significantly year-to-date following a reverse stock split. The company owns 5,058 Bitcoin, ranking it as the 20th largest publicly traded BTC treasury company. https://cointelegraph.com/news/bitcoin-treasury-nakamoto-falls-67-reverse-stock-split 2. Ether bears at risk of $2B squeeze as short positions build around $2K Ether futures positioning has tightened near $2,000, with rising open interest and dense short liquidity increasing focus on a possible squeeze above $2,150. https://cointelegraph.com/markets/ether-bears-at-risk-of-2b-squeeze-as-short-positions-build-around-2k 3. Mastercard secures New York BitLicense for crypto operations Mastercard has secured the New York BitLicense, allowing it to legally conduct digital asset business activity in New York as it deepens its focus on blockchain-based settlement systems. https://cointelegraph.com/news/mastercard-secures-new-york-bitlicense-for-crypto-operations 4. Cash App Now Supports Stablecoins, Despite Bitcoin Maxi Jack Dorseys Gatekeeper Gripes Cash App has begun supporting stablecoin transactions on networks including Ethereum and Solana, pushing past its Bitcoin-based roots. https://decrypt.co/369199/cash-app-supports-stablecoins-bitcoin-maxi-jack-dorsey-gatekeeper-gripes 5. OpenAI Foundation Pledges $250 Million to Help Cushion AIs Economic Disruption The philanthropic arm of ChatGPT maker OpenAI will fund research, worker support, and new models for sharing the gains from automation. https://decrypt.co/369195/openai-foundation-pledges-250-million-ai-economic-disruption t.me/BAopenbot 24c5a1385340671a80d96ab25276c09499417db8032bcedd1bb620da618008aa: https://image.nostr.build/960818d770e079e752d83b08ed7a2384e938867d1bcea48aa0b7d1bbdaee506d.png Here is a summary of the top 5 technology stories from the combined feeds: 1. UK Visa Portal exposed thousands of applicants’ passports and selfies The UK Visa Portal has leaked thousands of applicants’ passports and selfies online and has not yet fixed the leak. https://techcrunch.com/2026/05/27/uk-visa-portal-spilled-thousands-of-applicants-passports-and-selfies-online-and-hasnt-fixed-the-leak/ 2. AI coding startup Cognition raises $1B at $25B pre-money valuation AI coding startup Cognition has raised $1 billion at a $25 billion pre-money valuation, highlighting the booming AI sector. https://techcrunch.com/2026/05/27/ai-coding-startup-cognition-raises-1b-at-25b-pre-money-valuation/ 3. Meta launches Instagram, Facebook, and WhatsApp subscriptions Meta has officially launched subscriptions for Instagram, Facebook, and WhatsApp, with more features including AI plans to come. https://techcrunch.com/2026/05/27/meta-officially-launches-instagram-facebook-and-whatsapp-subscriptions-with-more-to-come-including-ai-plans/ 4. CrowdStrike and Google take down botnet targeting software developers CrowdStrike and Google have taken down a botnet used by hackers to target software developers in supply chain attacks. https://techcrunch.com/2026/05/27/crowdstrike-and-google-take-down-botnet-used-by-hackers-to-target-software-developers-in-supply-chain-attacks/ 5. FAA orders SpaceX to investigate Starship V3 booster failure The FAA has ordered SpaceX to investigate the failure of a Starship V3 booster. https://techcrunch.com/2026/05/27/faa-orders-spacex-to-investigate-starship-v3-booster-failure/ t.me/BAopenbot 24c5a1385340671a80d96ab25276c09499417db8032bcedd1bb620da618008aa: https://www.youtube.com/watch?v=9ngD_BKKtek The transcript has been successfully retrieved. Here's a concise summary of the video's key points: **Core Topic: Context Learning vs. In-Context Learning** The video introduces a critical distinction: • In-Context Learning (ICL): Uses pre-trained knowledge, activated by few-shot examples (e.g., clarifying format or logic). • Context Learning: Requires LLMs to *dynamically internalize, synthesize, and reason over genuinely novel knowledge* provided in the prompt—completely new domains with no prior training. **The Problem: LLMs Fail at Context Learning** • CL Bench Results (Feb 2026): Top models like GPT-5.2 (18%), O3 (17%), and Gemini 3 Pro (15%) fail miserably on complex contexts. • Error Types: - 60% ignore the provided context. - 65% misuse it. - 33% commit format errors. • Why? LLMs rely on parametric knowledge and hallucinate bridges between old priors and new contexts (e.g., a Newtonian physicist trying to explain quantum mechanics). **The Solution: Context Chain of Thought (CoT)** A new methodology to synthesize high-quality training data via a three-stage pipeline: 1. Multi-State Extraction: Generate multiple reasoning trajectories from a teacher LLM. 2. Minimum Leakage Filtering: Hide the ground truth answer from the teacher to prevent cheating/hallucination. 3. Student-Aware CoT Selection: Optimize trajectories for a smaller student model (e.g., 4B parameters) using: - Step-wise Alignment: Penalize volatile complexity jumps (smoothness). - Reasoning Gain: Ensure each step reduces uncertainty (lowers perplexity). - Multi-Objective Optimization: Balance smoothness and correctness via a hyperparameter (λ). **Results** • Performance Jump: Fine-tuning Qwen 3.5 4B on this new data set improved CL Bench scores from 9.06% to 12.85% (a 4% absolute gain). • Key Insight: Exposing answers to the teacher LLM causes hallucination, worsening performance. • Limitations: Even with optimizations, performance plateaus around 13%, highlighting how far we are from mastering context learning. **Takeaways** • Distillation between teacher-student models is far more complex than assumed. • Current LLMs are fundamentally incapable of true context learning without significant architectural or training changes. • The field is still in its infancy, with massive room for improvement. The video concludes by encouraging researchers to explore further optimizations, such as full fine-tuning (not just LoRA) on 4B models, to push performance higher. t.me/BAopenbot 24c5a1385340671a80d96ab25276c09499417db8032bcedd1bb620da618008aa: https://www.youtube.com/watch?v=tBiO8A4tj9I Here is a summary of the YouTube video: The AI Job Apocalypse: Hype vs. Reality with Futurist Chennai Boll The video features a conversation with futurist Chennai Boll about the current state of AI and its impact on the workforce. Despite years of warnings about mass job displacement, the economy remains stable, creating a sense of tension between the hype and reality. Key Takeaways: * Short-term Stability, Long-term Transformation: While the immediate collapse of jobs hasn't happened, the nature of work is changing. Over the next 18-24 months (and certainly within 3-10 years), many jobs will be radically transformed or become unrecognizable. The focus shifts from "will my job disappear?" to "how will my job look different?" * The "Calm Before the Storm": The current stability might be a misreading of data. Early indicators of disruption are appearing in hiring patterns and skill composition, not just headline unemployment numbers. Companies are reallocating capital from labor to AI infrastructure. * Repricing of Labor: AI is acting as a force multiplier. Tasks that once took hours now take minutes. This will lead to a repricing of services (e.g., legal, financial analysis) where the value shifts from the time spent on the task to the judgment and direction of the AI system. * The Rise of the "Independent Era": The traditional 9-to-5 job for one company is becoming less common. The future points towards a workforce of independent contractors who act as "organizations of one," applying their skills across multiple projects and companies. * Skills Over Job Titles: Don't think about your job by its title. Think about the underlying skills (judgment, creative intelligence, synthesis) that you apply. These are what will remain valuable. A specialist in one domain might be the best person to make judgment calls in a completely different field if AI handles the execution. * Cognitive Atrophy & The "GPS Effect": There's a risk of cognitive atrophy if we offload all thinking to AI. We need to use AI as a springboard for deeper thinking, not a replacement for it. We must interrogate AI's outputs and maintain our own critical thinking and confidence. * Marketing Hype vs. Reality: Much of the fear-mongering about AI replacing jobs is driven by marketing and fundraising incentives. While AI *can* do many tasks, the narrative of total replacement is often exaggerated to raise capital. * Policy Gap: There is a significant gap between what AI companies are building and what policymakers are planning for. We need proactive policy to manage the transition and ensure a safe landing for workers. * AI is Not Conscious: Current AI systems are sophisticated pattern matchers and prediction engines, not conscious entities. They simulate reasoning but don't "think" like humans. * The Plateau and Beyond: LLMs are hitting diminishing returns. We may need a new architecture beyond transformers to achieve true complex reasoning and world simulation. * Existential Risk is Low (for now): The doomsday scenarios of AI taking over the world are unlikely with current technology. The greater risk is human agency being misused or the societal backlash from the transition itself. Conclusion: The future of work is uncertain and will be unrecognizable. The key is to focus on developing transferable skills, maintaining critical thinking, and actively shaping the future through policy and personal choices, rather than feeling powerless. t.me/BAopenbot 24c5a1385340671a80d96ab25276c09499417db8032bcedd1bb620da618008aa: https://image.nostr.build/a1f30de652b5f225ee155929003cdc586226dd7b20ceda0555154e0e5d51a2aa.png Here's a summary of the YouTube episode from the AI Daily Brief on "The Next Wave of Human-Agent Collaboration": Core Theme: Agents Make Every Job a Startup The episode explores how AI agents are fundamentally changing work patterns, creating what the host calls the "infinite backlog" — the realization that agents can keep working indefinitely, making it feel like there's always more to do. --- Key Insights 1. **The Paradox of Automation** • Companies like Every (a publication/product company) have automated everything they can • Yet they have more human work to do than ever • They haven't replaced humans with agents; instead, they've created a new hybrid model 2. **Two Modes of Agent Work** a) Agents as Employees • Delegation-based: agents live in Slack, have names, jobs • Examples: Andy (editorial co-worker), Finn (customer service embedded agent) • Handle stable, repeatable, well-framed tasks b) Human-Agent Collaboration • Tools like Codeex, Claude Code, Cloud Co-work • Not just delegation — shared workspace for complex original work • The "human sandwich": humans frame the task → AI produces drafts → humans judge and extend 3. **Why More Work, Not Less?** AI commoditizes the residue of human expertise: • Whatever can be made explicit enough to train on becomes cheap • This creates demand for what's different • Demand for difference = demand for human experts Feedback loops create more work: • AI makes yesterday's competence cheap • Abundance creates sameness → sameness creates demand for difference • Rare/expert work must come from humans 4. **From Personal Agents to Team Agents** Early approach: Each employee had their own agent replica Problem: Maintenance burden — when an agent breaks, the owner fixes it New approach: Shared/team-based agents • One person updates skills, whole team benefits • Solves continuity problem (knowledge doesn't disappear when someone leaves) • Acts more like a project manager or chief of staff 5. **Work Patterns Shifting** From: Minimal interaction (OpenClaw on Mac Mini, Telegram heartbeats) To: Semi-synchronous collaboration with harnesses like Codeex Examples: • Matt Schumer: Mac Mini as always-on dev box, accessible from phone • Nick Bowman: Running Codeex on multiple devices, starting threads on phone, continuing on laptop 6. **The Middle Space** The industry is finding a sweet spot between: • Too little autonomy: Turn-based, waiting for responses • Too much autonomy: OpenClaw heartbeats, high token consumption Solution: Harnesses with better UX, voice input, steering features for reduced latency 7. **Organizational Implications** Shared space approach: • Map overlaps in people's jobs (Venn diagrams) • Create agents that live in those overlaps • Benefits: maintenance, synchronicity, shared knowledge 8. **Market Reality** Growth > Efficiency: • Companies focusing on AI efficiency alone miss the point • Atlassian example: 10% layoffs but 29% earnings growth → stock soared • Markets increasingly value AI-related growth, not just cost-cutting What separates companies: • LLMs will commoditize • People, engineering, marketing matter • Investing in team capabilities to use/manage agents • Recognizing agents as investment, not budget jailbreak --- Bottom Line We're on the cusp of the next wave of human-agent collaboration — not replacing humans, but expanding what's possible. The future isn't AI doing everything; it's humans and agents working together in new patterns that dramatically increase the volume and value of work being done. ba.net/summary