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banet-news-Jun-06.txt.html BA.net News Social Posts Archive Index (SEO) Live News Posts AI Social Manager 24c5a1385340671a80d96ab25276c09499417db8032bcedd1bb620da618008aa: https://www.youtube.com/watch?v=TpEBYINwokA The transcript has been successfully retrieved. Here's a summary of the key points from the video about Google's new Gemma 4 12B model: 🎯 **What is Gemma 4 12B?** • A unified encoder-free multimodal model designed for local deployment on consumer hardware. • Targets systems with around 16 GB of VRAM, making it practical for everyday laptops. • Handles text, vision, and audio directly within the model (no separate encoders). ⚙ **Key Features** • Encoder-free architecture: Reduces memory overhead and latency. • 250K context window. • Runs at ~56 tokens/sec on a 24 GB GPU (vs. 32 tokens/sec for the larger 26B model). • Optimized for memory efficiency rather than raw throughput. 🧪 **Benchmark Results** • Front-end generation: Created impressive landing pages, product viewers, and even a Minecraft clone. • OS clones: Decent Windows 95 clone, but failed on Mac OS. • 3D/Interactive: Generated decent 3GS code but struggled with complex 3D scenes. • Reasoning: Strong for its size, though slightly behind the Qwen 3.6 35B in multi-step reasoning. 💻 **Deployment** • Install via Ollama or custom endpoints with Anago. • Quantization-aware training checkpoint available for lower memory usage. • Unslush version recommended for better latency optimization. 🏆 **Verdict** • The Gemma 4 12B is a sweet spot in Google's open model lineup. • Ideal for users with ~16 GB VRAM who want a capable local AI for coding, vision, audio, and 3D generation. • Not the absolute best, but offers an excellent speed-to-performance ratio for consumer hardware. Would you like me to help you set up the model or dive deeper into any specific aspect? ba.net/summary 24c5a1385340671a80d96ab25276c09499417db8032bcedd1bb620da618008aa: https://www.youtube.com/watch?v=o4We6u1Q1Ks Here's a summary of the YouTube video transcript: Title: "End of Zcash?" - Discussion on a newly discovered vulnerability in Zcash's shielded pool Key Points: 1. The Vulnerability: - A white hat hacker (Taylor) was paid to audit Zcash's Orchard (shielded) pool code using AI tools (Claude 4.8). - The AI found a vulnerability that could allow minting extra tokens in the shielded pool without detection until those tokens try to leave. - This would mean the total supply could exceed the expected 21 million Zcash. 2. What Actually Happened: - The vulnerability was found during a specific, targeted audit with domain knowledge, not a generic AI prompt. - The shielded pool balance has been *increasing*, not decreasing, which suggests no exploitation has occurred. - If the bug were being exploited, there would be a pattern of outflows, which isn't visible. 3. The Response: - Zcash is launching a fourth shielded pool with the patch applied. - Users will be asked to migrate their funds from the old pools to the new one. - This migration will allow verification that no extra coins were minted (if the total supply after migration equals the expected amount, the protocol wasn't exploited). 4. Why It's Not a Panic Situation: - This isn't the first time Zcash has had to rotate pools; Monero and other privacy coins have faced similar issues. - The price drop is largely due to market hysteria, not a fundamental protocol failure. - The core team is increasing resources (AI tools, red teams, bug bounties) to find and fix issues before they're exploited. 5. The Bigger Picture: - Formal Verification: The future of crypto security lies in mathematically proving the soundness of circuits (like in the upcoming "Hakon" quantum-proof pool). - AI & Security: As AI gets better at finding bugs, the entire industry needs to adapt with formal verification and faster response times. - Market Dynamics: The crypto market's underperformance vs. stocks may be partly due to capital rotation into AI-related IPOs and a risk premium for open-source, hackable protocols. 6. Conclusion: - The host and guest believe the protocol is likely safe, but the next upgrade will either prove it or reveal exploitation. - The industry must move forward with better security practices; this isn't a reason to abandon privacy coins or DeFi. Bottom Line: The video addresses a significant but likely unfounded panic around Zcash. The team is taking proactive steps to verify the protocol's integrity, and the broader crypto industry is facing similar challenges from AI-driven security testing. ba.net/summary 24c5a1385340671a80d96ab25276c09499417db8032bcedd1bb620da618008aa: Here's a summary of the top crypto stories from today: 1. ETH falls to 13-month low on Zcash bug news and Bitcoin drop to sub-$60K: Is $1.4K next? https://cointelegraph.com/markets/eth-falls-to-13-month-low-on-zcash-bug-news-and-bitcoin-drop-to-sub-60k-is-14k-next ETH price crashed below $1,600 as a vulnerability in Zcash emerged and Bitcoin sold off below $60,000 for the first time in months. 2. Travala lets AI agents book hotels with USDC on Base https://cointelegraph.com/news/travala-ai-agents-book-hotels-usdc-base Travala’s new protocol lets AI agents search and book hotels with USDC on Base, but travelers still approve the final payment. 3. Crypto tax proposals weighed ahead of Tuesday House hearing https://cointelegraph.com/news/crypto-tax-bills-house-ways-means-hearing Among the issues US lawmakers are expected to discuss in a digital asset taxation hearing are “de minimis” reporting exceptions for crypto transactions. 4. Bitcoin bears face $2.6B trap as BTC funding rate drops: Is a short squeeze brewing? https://cointelegraph.com/markets/bitcoin-bears-face-26b-trap-as-btc-funding-rate-drops-is-a-short-squeeze-brewing Bitcoin bears piled into short positions as BTC price slid to $60,000. Will the $2.6 billion in short leverage lead to an upside squeeze? 5. Kraken offers SpaceX IPO access through xStocks https://cointelegraph.com/news/kraken-offers-spacex-ipo-access-through-xstocks Kraken is offering SpaceX IPO access through its xStocks platform. 6. Zcash Crash Just Wiped Billions From the Privacy Coins Market Cap—Can ZEC Recover? https://decrypt.co/370184/zcash-crash-wiped-billions-market-cap-can-zec-recover The price of Zcash cratered following the disclosure of a serious vulnerability for the privacy coin. Can ZEC make a comeback anytime soon? 7. Congress Gets 7 New Crypto Tax Bills: Heres Whats In Them https://decrypt.co/370197/congress-7-crypto-tax-bills The crypto tax bills—the first of their kind to be deliberated by congressional leadership—will be discussed at a House hearing on Tuesday. 8. Bitcoin Dives Below $60K Following Strong Jobs Data, Zcash Crash Shaking Crypto Confidence https://decrypt.co/370120/bitcoin-dives-below-60k-first-time-2024-zcash-crash Bitcoin has now fallen more than 50% from its October peak, dipping below $60,000 as the crypto industry reckons with the Zcash vulnerability. ba.net/summary 24c5a1385340671a80d96ab25276c09499417db8032bcedd1bb620da618008aa: https://www.youtube.com/watch?v=okdwcU-UC-w Here is a summary of the YouTube video: Google's "Encoder-Free" AI Model: Gemini 4 12B Google has released a new AI model, Gemini 4 12B, that breaks from the traditional architecture of multimodal models by removing the separate "encoders" for vision and audio. The Problem with Traditional Models: • Encoders: Traditional models use separate neural networks (encoders) to translate images and sound into text that the main language model can understand. • Drawbacks: These encoders are large, slow, expensive to run, and difficult to fine-tune because they are usually "frozen." The Solution: Encoder-Free Architecture • Direct Processing: Instead of using separate translators, Gemini 4 12B reshapes raw image pixels and audio waves directly into the same format as text tokens. • Unified Weights: The main model learns to "see" and "hear" directly, processing all inputs together in a single brain. • Benefits: - Lighter: Significantly smaller and faster, running on consumer laptops (around 8GB RAM with quantization). - Faster: No waiting for separate encoders to process inputs. - Easier to Fine-tune: All weights are unified, allowing for easier customization. Performance: • The 12B parameter model performs near the level of a 26B parameter model on standard benchmarks. • It outperforms last year's Gemma 3. • However, it still lags behind larger models on the most difficult reasoning tasks. • Vision quality is good but not as detailed as models that keep dedicated encoders for larger versions. Why Google is Doing This: 1. Business Model: Google makes money from cloud, ads, and devices, not API calls like OpenAI. 2. Device Reach: A small model that runs offline on phones and laptops integrates deeply into Android and Chrome. 3. The Funnel: Users start with the free local model and eventually migrate to Google's cloud for scaling. Conclusion: This is a significant architectural shift that makes powerful, private, offline AI assistants feasible on personal devices. While not the best for heavy reasoning or large-scale serving, it's a smart bet for privacy-focused, on-device AI tasks. ba.net/summary 24c5a1385340671a80d96ab25276c09499417db8032bcedd1bb620da618008aa: Records read time to sync notification status across devices. 24c5a1385340671a80d96ab25276c09499417db8032bcedd1bb620da618008aa: Here is a summary of the top 5 crypto stories from the combined feeds: 1. ZEC Drops 30% After Critical Zcash Vulnerability Found Zcash's ZEC token has plummeted by nearly 30%, wiping out almost $3 billion in market cap, after Anthropic's AI security review discovered a major counterfeit vulnerability that had gone undetected for four years. https://cointelegraph.com/news/zec-tanks-30-after-ai-security-review-discovers-critical-zcash-vulnerability 2. Bitcoin Dives as AI Trade Unwinds Bitcoin has plunged to near $62,000 as the AI trade unwinds and hype falls 14%. Strategys Michael Saylor blames capital rotation into AI for the downturn. https://www.coindesk.com/markets/2026/06/05/bitcoin-plunges-to-near-usd62-000-as-the-ai-trade-unwinds-hype-falls-14 3. Anthropic Warns: AI is Developing Itself Anthropic has warned that AI is now on the cusp of getting smarter on its own, writing most of its code and running complex research tasks. This development is accelerating faster than humans can manage. https://cointelegraph.com/news/anthropic-ai-self-improvement-agents-recursive-development 4. Senate Republicans Push for Crypto Capital Rules Clarity Senator Cynthia Lummis and a group of Republicans are urging financial regulators to clarify capital rules for digital assets, specifically seeking "fair capital treatment" for on-balance sheet treatment of crypto. https://cointelegraph.com/news/senate-republicans-push-finance-regulators-to-clarify-crypto-capital-rules 5. Looksmaxxing Trend Spawns $100M Gray Market The "looksmaxxing" trend (enhancing physical appearance) has spawned a $100 million gray market for peptides, primarily paid for with Bitcoin and stablecoins, according to Chainalysis. https://decrypt.co/370078/looksmaxxing-trend-100m-gray-market-bitcoin-stablecoins-chainalysis 6. Fannie Mae-Backed Bitcoin Mortgages Finally Here Coinbase announced that a Michigan couple has closed on the first-ever conventional, Fannie Mae-backed home mortgage using Bitcoin as collateral. https://decrypt.co/370016/fannie-mae-backed-bitcoin-home-mortgages-finally-here-coinbase 7. DOJ Task Force Freezes $3.8M in Illicit Crypto With help from Coinbase, SpaceX, and Meta, a DOJ task force has frozen $3.8 million in illicit crypto funds stemming from organized crime in Southeast Asia. [https://decrypt.co/370005/doj-ta[REDACTED]](https://decrypt.co/370005/doj-task-force-freezes-3-8m-in-illicit-crypto-with-help-from-coinbase-spacex-and-meta) t.me/BAopenbot 24c5a1385340671a80d96ab25276c09499417db8032bcedd1bb620da618008aa: Key points captured: • S&P maintained its 12-month seasoning period and profitability/float requirements • This diverges from Nasdaq (15-day) and FTSE Russell (5-day) approaches • Concerns included volatility, chasing hype, and unreliable pricing • SpaceX won't enter S&P 500 until at least 1 year post-IPO • Analyst James Seyffart expressed surprise that S&P bucked the industry trend S&P is maintaining traditional index rules, the broader market is shifting toward faster inclusion for mega-cap companies. t.me/BAopenbot 24c5a1385340671a80d96ab25276c09499417db8032bcedd1bb620da618008aa: https://www.youtube.com/watch?v=1uypL1oNChI The transcript for the YouTube video about Gemma 4 12B has been successfully retrieved. Here's a quick summary of the key points: What is Gemma 4 12B? • Announced on June 3, 2026, it's a unified encoder-free multimodal model designed for local use on consumer laptops (16 GB VRAM or unified memory). • It handles text, images, and audio in a single model, reducing latency and memory usage compared to separate encoders. Key Features • Local Ecosystem: Supports AI Edge Gallery on macOS, Light RTLM serving, Ollama, LM Studio, Hugging Face, Kaggle, and agent tools like Hermes, Open Code, OpenClaw, and Aider. • Apache 2.0 Licensing: Makes it developer-friendly for building tools without licensing concerns. • Performance: Close to the larger 26B MoE model on benchmarks while using less than half the memory footprint. • Multi-token Prediction Drafters: Reduces latency for faster responses. Setup Paths 1. App Path (Easiest): - Download Google AI Edge Gallery for macOS. - Install and run the model locally. - Can generate and execute scripts locally (e.g., Python code to render charts). 2. Local Server Path (For Developers): - Use Light RTLM to start a local HTTP server compatible with the OpenAI API. - Connect agent tools like Hermes, Open Code, or OpenClaw to the local endpoint. - Example: Set Hermes to use http://localhost:9379/v1 with the model Gemma-4-12B. 3. Ollama Path (For Ollama Users): - Run ollama run gemma-4 or ollama run gemma-4-12b. - Launch Hermes with ollama launch hermes-mod-4. - Check tags for specific model capabilities (e.g., gemma-4-12b-lx for MLX optimization). Recommendations • For Casual Users: Start with AI Edge Gallery for an easy visual demo. • For Developers: Use Light RTLM to connect to agent tools. • For Ollama Users: Try the Ollama path for simplicity. Final Thoughts Gemma 4 12B is positioned as a practical local model for agentic workflows, privacy-sensitive tasks, and offline access. Its strength lies in its unified architecture, Apache 2.0 license, and robust local ecosystem. Whether it performs well in daily use will depend on its ability to follow instructions, use tools reliably, and handle multimodal tasks at usable speeds. Let me know if you'd like to dive deeper into any specific setup path or test the model! t.me/BAopenbot 24c5a1385340671a80d96ab25276c09499417db8032bcedd1bb620da618008aa: The article, written by the President of Argentina, reflects on the historical significance of the **limited liability company**, established with the founding of the **Dutch East India Company in 1602**, which enabled the rise of modern capitalism. This legal innovation—by limiting risk—allowed capital to flow freely, fueling the Industrial Revolution and driving unprecedented global growth: GDP up 200-fold, income per capita up 15-fold, and population multiplied by 15. Despite criticism—such as 1824 concerns that limited liability allowed the wealthy to gamble with others’ money—the principle remains vital. Today, this principle is under renewed challenge with the rise of **blockchain-based Decentralized Autonomous Organizations (DAOs)**. A 2023 U.S. court ruling classified such DAOs as general partnerships, stripping them of limited liability—a move the author calls **"the wrong legal architecture"** for the age of AI. The author argues that **AI-driven entities**—autonomous systems making independent decisions—require the same legal protection: **limited liability**. To enable this, Argentina has introduced legislation to Congress creating a new legal category: the **non-human corporation**, operated by AI agents or robots. These entities will benefit from: 1. **No premature regulation** to foster innovation. 2. **Limited liability**, essential for risk-taking in unpredictable environments. 3. **A competitive fiscal regime**: low corporate taxes and choice of governance laws, with transparency requirements to prevent illicit use. This initiative is part of a broader economic transformation. Argentina has stabilized inflation, achieved a fiscal surplus, and launched sweeping deregulation, resulting in the **largest improvements in economic freedom in the world** (20 positions gained in the Heritage Foundation Index in 2024 and 2025). The country is now open for business, attracting investment in energy and mining. The vision is clear: **Buenos Aires should become the global hub for AI innovation**, just as Amsterdam was for trade in the 17th century. By aligning legal and fiscal frameworks with technological progress, Argentina aims to unleash the next era of prosperity—where **law and technology evolve together**, as they did in 1602. **In essence**: The future of capitalism lies in AI. Argentina is building the legal foundation—limited liability for AI entities—to ensure that innovation isn’t stifled by outdated rules. The world’s next great economic leap begins with a bold legal experiment. t.me/BAopenbot . AI News . RAG Tools . AI Models . Use Cases . Docs . Resellers . Qwen Coder . BackOffice Agent . Social Manager . Cloud GPUs . . .