اکنون در دسترس! پژوهش تلگرام ۲۰۲۵ — مهمترین بینشهای سال 
Data Science, Machine Learning, AI & IOT
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Posts from world's largest datascientists community and latest trends learning articles in Machine learning, deep learning, AI, IOT and tools Part of @nuggetsnetwork Instagram: kdnuggets Chat @datasciencechats Admin: @LordAdminBot
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📊 شاخصهای مخاطب و پویایی
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📝 توضیح و سیاست محتوایی
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پستهای کانال
🔬 AI Research Digest
📅 Week of Jun 3–Jun 9, 2026
━━━━━━━━━━━━━━━━━━━━━━━━
1. 🤖 OpenClaw — Local-First Personal AI Assistant
Authors/Org: openclaw | GitHub: openclaw/openclaw
Bottleneck solved: Removes cloud dependency by running AI entirely on your own devices while connecting to 50+ messaging platforms (Telegram, Slack, WhatsApp, Discord, and more).
With 377K+ stars and explosive growth since January 2026, OpenClaw is becoming the go-to local AI gateway — ideal for developers who want privacy-first automation across every chat surface they already use.
🔗 OpenClaw on GitHub
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2. ⏱️ TimeMaster — Time-Series Reasoning via Reinforcement Learning
Authors/Org: Feng Lang et al. | arXiv: 2506.13705
Bottleneck solved: Enables multimodal LLMs to reason accurately over visualized time-series data (ECG, EMG, HAR) using a composite RL reward that balances format, accuracy, and insight quality.
A 3B-parameter TimeMaster model beats GPT-4o and Qwen2.5-7B on time-series benchmarks — huge win for data teams working with sensor, financial, or health signal data.
🔗 TimeMaster on arXiv
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3. 🔄 Bridging Offline and Online RL for LLMs
Authors/Org: Jack Lanchantin, Angelica Chen, Janice Lan et al. (Meta) | arXiv: 2506.21495
Bottleneck solved: Clarifies when to use offline vs. online RL fine-tuning for LLMs, showing online/semi-online methods consistently outperform offline across both verifiable math and open-ended instruction following.
The key practical finding: multi-tasking with verifiable and non-verifiable rewards jointly boosts performance across both task types — a recipe developers can apply directly to RLHF pipelines.
🔗 Bridging Offline and Online RL for LLMs on arXiv
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💡 Stay curious. Read the papers.
For More: @kdnuggets @datasciencechats
| 2 | 🤖 AI & Data Science Weekly Digest
📅 Week of Jun 2–Jun 8, 2026
━━━━━━━━━━━━━━━━━━━━━━━━
1. 🚀 MiniMax M3 Slashes Multimodal Compute by 20x
MiniMax M3 is a new multimodal model supporting up to 1 million tokens while cutting per-token compute requirements to just 1/20th of previous models, with 9x faster prefilling and 15x faster decoding at 1M context. For data teams processing long documents, codebases, or large datasets, this makes million-token context practically affordable for production use.
🔗 LLM Stats – AI Model Releases June 2026
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2. 💸 Orion-100B: 100B-Parameter Model Trained at $1.25/Hour
Orion-100B demonstrated that training a 100-billion-parameter model can now cost as little as $1.25/hour, a dramatic drop that fundamentally changes the economics of large-scale AI development. This opens the door for mid-sized engineering teams and startups to fine-tune or replicate frontier-scale models without enterprise budgets.
🔗 AI News June 2026 – AI Startup Edge
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3. 🧠 GPT-5.5 Instant, Gemini 3.5 Flash & Claude Opus 4.8 Set New Benchmarks
OpenAI, Google, and Anthropic each released updated frontier models this week — GPT-5.5 Instant, Gemini 3.5 Flash, and Claude Opus 4.8 — all pushing new performance ceilings on reasoning, coding, and multimodal tasks. Developers building AI-powered applications should evaluate which model best fits their latency, cost, and capability tradeoffs with these new baselines.
🔗 LLM Updates June 2026 – LLM Stats
━━━━━━━━━━━━━━━━━━━━━━━━
4. 🔐 Prompt Injection Attacks Officially Classified as CVE Category
Prompt injection vulnerabilities have been formally recognized as a CVE category, and AI-generated code CVEs are up nearly 6x compared to 2025 — a signal that AI-assisted development carries real security debt. Software teams should integrate prompt injection testing into their security review pipelines and audit any LLM-integrated endpoints for input sanitization gaps.
🔗 AI News Briefs – Radical Data Science June 2026
━━━━━━━━━━━━━━━━━━━━━━━━
5. 📊 Databricks 2026 Data + AI Summit: 30,000 Professionals Descend on SF
Databricks announced the full agenda for its 2026 Data + AI Summit, set for June 15–18 at the Moscone Center in San Francisco, with over 30,000 data and AI professionals expected to attend. The summit will cover the latest in data lakehouses, MLOps, real-time AI, and enterprise AI governance — essential viewing for data engineers and ML teams.
🔗 Databricks 2026 Data + AI Summit Announcement
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💡 Stay ahead. Stay curious.
For More: @kdnuggets @datasciencechats | 540 |
| 3 | 🔬 AI Research Digest
📅 Week of May 27–Jun 2, 2026
━━━━━━━━━━━━━━━━━━━━━━━━
1. 📱 MobileGym: Verifiable & Parallel Mobile GUI Agent Simulation
Authors/Org: Chinese Academy of Sciences, Peking University, CUHK | arXiv: 2605.26114
Bottleneck solved: Training mobile GUI agents at scale is blocked by slow, non-deterministic simulators with no reliable reward signal.
MobileGym runs 256 parallel Android instances in-browser, uses JSON state for bit-exact reproducibility, and ships 416 task templates with sub-millisecond judges — lifting Qwen3-VL-4B real-device pass rate from 32% → 73% with GRPO fine-tuning on a single 3×RTX node.
🔗 arXiv 2605.26114
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2. 🦞 AutoResearchClaw: Self-Reinforcing Autonomous Research with Human-AI Collaboration
Authors/Org: Aiming Lab | arXiv: 2605.20025
Bottleneck solved: Fully autonomous research pipelines hallucinate results and lack a principled way to incorporate human oversight without defeating the purpose of automation.
AutoResearchClaw combines structured multi-agent debate, a self-healing executor with Pivot/Refine loops, and seven human-in-the-loop intervention modes — outperforming AI Scientist v2 by 54.7% on ARC-Bench while preventing fabricated citations via live literature grounding.
🔗 arXiv 2605.20025
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3. 🧠 nanochat: Full-Stack LLM Training Pipeline for ~$100
Authors/Org: Andrej Karpathy | GitHub: karpathy/nanochat
Bottleneck solved: End-to-end LLM training (pretraining → RLHF → chat UI) has no minimal, hackable reference implementation that a single developer can run affordably.
Unlike nanoGPT which stops at pretraining, nanochat covers tokenization, SFT, evaluation, inference, and a ChatGPT-like UI in one dependency-minimal codebase — reaching GPT-2 capability in ~$48 of cloud GPU time.
🔗 github.com/karpathy/nanochat
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💡 Stay curious. Read the papers.
For More: @kdnuggets @datasciencechats | 988 |
| 4 | 🤖 AI & Data Science Weekly Digest
📅 Week of May 26–June 1, 2026
━━━━━━━━━━━━━━━━━━━━━━━━
1. 🧠 Anthropic Releases Claude Opus 4.8 with Faster, Cheaper Inference
Anthropic launched Claude Opus 4.8, featuring stronger benchmarks, improved honesty, dynamic workflows in Claude Code, and a fast mode that runs at 2.5× the speed of previous models at one-third the cost. Data and engineering teams get a meaningfully cheaper path to high-capability agentic workflows without sacrificing quality.
🔗 Anthropic Release Notes – May 2026
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2. 🔧 Anthropic Acquires Stainless, the Dev-Tools Startup Behind OpenAI and Google SDKs
Anthropic acquired Stainless, whose tooling auto-generates idiomatic SDKs and is already used by OpenAI, Google, and Cloudflare to ship client libraries. This gives Anthropic direct control over the developer experience layer, signaling a deeper push to own the full API toolchain.
🔗 Anthropic has acquired the dev tools startup used by OpenAI, Google, and Cloudflare – TechCrunch
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3. 🤖 Claude Managed Agents Now Support Private MCP Servers and Custom Sandboxes
Anthropic's Claude Managed Agents can now run inside a developer-controlled sandbox while connecting to private Model Context Protocol (MCP) servers, with the agent loop remaining on Anthropic's infrastructure. This hybrid architecture lets teams integrate proprietary data and tools into production agents without exposing sensitive resources externally.
🔗 Google IO 2026 and Anthropic advance agentic AI for businesses
━━━━━━━━━━━━━━━━━━━━━━━━
4. ⚡ AMD EPYC "Venice" Enters Production on TSMC 2nm — First HPC Chip at This Node
AMD began production ramp of its 6th Gen EPYC "Venice" processor on TSMC's 2nm process, making it the first high-performance computing product at this fabrication node. Better performance-per-watt and higher transistor density directly benefit data center operators running AI inference and large-scale data pipelines under tight power budgets.
🔗 AMD Announces Production Ramp of Next-Generation AMD EPYC Processor "Venice" on TSMC 2nm
━━━━━━━━━━━━━━━━━━━━━━━━
5. 💻 OpenAI Codex Reaches 4 Million Active Users Powered by GPT-5.5
OpenAI's Codex coding agent, now running on GPT-5.5, has hit 4 million active users — reflecting rapid enterprise adoption of AI-assisted software development. For developer and data teams, this signals that agentic coding tools are moving from novelty to standard workflow infrastructure.
🔗 OpenAI and Anthropic news from the past week (Week 20, 2026)
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💡 Stay ahead. Stay curious.
For More: @kdnuggets @datasciencechats | 880 |
| 5 | 🤖 AI & Data Science Weekly Digest
📅 Week of May 25–May 31, 2026
━━━━━━━━━━━━━━━━━━━━━━━━
1. ⚡ Google Launches Gemini 3.5 Flash at I/O 2026
Google released Gemini 3.5 Flash — a frontier model that's 4x faster than comparable models and optimized for agentic workflows, coding, and multimodal tasks. Developers can access it via the Gemini API with 1M token context at $1.50/$9 per 1M tokens, and the new Managed Agents feature lets a single API call spin up a full reasoning agent with tool use and code execution.
🔗 Google Introduces Gemini 3.5 Flash at I/O 2026
━━━━━━━━━━━━━━━━━━━━━━━━
2. 📢 OpenAI Opens ChatGPT Ad Platform to All Businesses
OpenAI launched a self-serve Ads Manager at ads.openai.com, eliminating the previous $50,000 minimum spend and introducing CPC bidding, a Conversions API, and pixel-based tracking. This shifts ChatGPT from a subscription-only product toward a major ad-supported platform — opening new acquisition channels for data teams and developer-focused SaaS companies.
🔗 OpenAI launches self-serve ad platform
━━━━━━━━━━━━━━━━━━━━━━━━
3. 🧬 PolyU Researchers Store Data in Engineered Proteins
The Hong Kong Polytechnic University pioneered a method to store and retrieve digital data using de novo designed unnatural proteins, offering a radically denser and more stable storage medium as AI-generated data volumes explode. For data teams, this signals a new frontier in long-term archival storage that could complement or eventually compete with DNA and tape-based cold storage.
🔗 Data explosion in AI era: PolyU leads breakthroughs in protein-based data storage
━━━━━━━━━━━━━━━━━━━━━━━━
4. 💡 Light-Based Computing Could Slash AI Energy Costs
Penn researchers created a hybrid light-matter particle (polariton) system that dramatically accelerates AI inference while consuming far less energy than silicon-based hardware. This matters for data teams running large-scale model inference, where energy cost and latency are growing operational constraints.
🔗 Breakthroughs in AI Innovations for May 2026
━━━━━━━━━━━━━━━━━━━━━━━━
5. 🛡️ Five Nations Release Agentic AI Security Guidance
Cybersecurity agencies from the US, UK, Australia, Canada, and New Zealand jointly published guidance on "Careful Adoption of Agentic AI Services," covering risks like prompt injection, over-permissioned agents, and supply chain attacks. Software teams deploying AI agents in production should treat this as a practical security checklist before rollout.
🔗 7 Explosive AI Updates in May 2026
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💡 Stay ahead. Stay curious.
For More: @kdnuggets @datasciencechats | 455 |
| 6 | 🤖 *AI & Data Science Weekly Digest*
📅 Week of May 25–May 31, 2026
━━━━━━━━━━━━━━━━━━━━━━━━
**1. ⚡ Google Launches Gemini 3.5 Flash at I/O 2026**
Google released Gemini 3.5 Flash — a frontier model that's 4x faster than comparable models and optimized for agentic workflows, coding, and multimodal tasks. Developers can access it via the Gemini API with 1M token context at $1.50/$9 per 1M tokens, and the new Managed Agents feature lets a single API call spin up a full reasoning agent with tool use and code execution.
🔗 [Google Introduces Gemini 3.5 Flash at I/O 2026](https://www.marktechpost.com/2026/05/20/google-introduces-gemini-3-5-flash-at-i-o-2026-a-faster-and-cheaper-model-for-ai-agents-and-coding/)
━━━━━━━━━━━━━━━━━━━━━━━━
**2. 📢 OpenAI Opens ChatGPT Ad Platform to All Businesses**
OpenAI launched a self-serve Ads Manager at ads.openai.com, eliminating the previous $50,000 minimum spend and introducing CPC bidding, a Conversions API, and pixel-based tracking. This shifts ChatGPT from a subscription-only product toward a major ad-supported platform — opening new acquisition channels for data teams and developer-focused SaaS companies.
🔗 [OpenAI launches self-serve ad platform](https://www.axios.com/2026/05/05/openai-self-serve-ad-platform)
━━━━━━━━━━━━━━━━━━━━━━━━
**3. 🧬 PolyU Researchers Store Data in Engineered Proteins**
The Hong Kong Polytechnic University pioneered a method to store and retrieve digital data using de novo designed unnatural proteins, offering a radically denser and more stable storage medium as AI-generated data volumes explode. For data teams, this signals a new frontier in long-term archival storage that could complement or eventually compete with DNA and tape-based cold storage.
🔗 [Data explosion in AI era: PolyU leads breakthroughs in protein-based data storage](https://www.eurekalert.org/news-releases/1129790)
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**4. 💡 Light-Based Computing Could Slash AI Energy Costs**
Penn researchers created a hybrid light-matter particle (polariton) system that dramatically accelerates AI inference while consuming far less energy than silicon-based hardware. This matters for data teams running large-scale model inference, where energy cost and latency are growing operational constraints.
🔗 [Breakthroughs in AI Innovations for May 2026](https://www.aiandnews.com/blog/latest-ai-news-may-2026-3/)
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**5. 🛡️ Five Nations Release Agentic AI Security Guidance**
Cybersecurity agencies from the US, UK, Australia, Canada, and New Zealand jointly published guidance on "Careful Adoption of Agentic AI Services," covering risks like prompt injection, over-permissioned agents, and supply chain attacks. Software teams deploying AI agents in production should treat this as a practical security checklist before rollout.
🔗 [7 Explosive AI Updates in May 2026](https://imfounder.com/science-tech/ai/ai-updates-may-2026/)
━━━━━━━━━━━━━━━━━━━━━━━━
💡 *Stay ahead. Stay curious.*
For More: @kdnuggets @datasciencechats | 34 |
| 7 | 🤖 *AI & Data Science Weekly Digest*
📅 Week of May 25–May 31, 2026
━━━━━━━━━━━━━━━━━━━━━━━━
**1. ⚡ Google Launches Gemini 3.5 Flash at I/O 2026**
Google released Gemini 3.5 Flash — a frontier model that's 4x faster than comparable models and optimized for agentic workflows, coding, and multimodal tasks. Developers can access it via the Gemini API with 1M token context at $1.50/$9 per 1M tokens, and the new Managed Agents feature lets a single API call spin up a full reasoning agent with tool use and code execution.
🔗 [Google Introduces Gemini 3.5 Flash at I/O 2026](https://www.marktechpost.com/2026/05/20/google-introduces-gemini-3-5-flash-at-i-o-2026-a-faster-and-cheaper-model-for-ai-agents-and-coding/)
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**2. 📢 OpenAI Opens ChatGPT Ad Platform to All Businesses**
OpenAI launched a self-serve Ads Manager at ads.openai.com, eliminating the previous $50,000 minimum spend and introducing CPC bidding, a Conversions API, and pixel-based tracking. This shifts ChatGPT from a subscription-only product toward a major ad-supported platform — opening new acquisition channels for data teams and developer-focused SaaS companies.
🔗 [OpenAI launches self-serve ad platform](https://www.axios.com/2026/05/05/openai-self-serve-ad-platform)
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**3. 🧬 PolyU Researchers Store Data in Engineered Proteins**
The Hong Kong Polytechnic University pioneered a method to store and retrieve digital data using de novo designed unnatural proteins, offering a radically denser and more stable storage medium as AI-generated data volumes explode. For data teams, this signals a new frontier in long-term archival storage that could complement or eventually compete with DNA and tape-based cold storage.
🔗 [Data explosion in AI era: PolyU leads breakthroughs in protein-based data storage](https://www.eurekalert.org/news-releases/1129790)
━━━━━━━━━━━━━━━━━━━━━━━━
**4. 💡 Light-Based Computing Could Slash AI Energy Costs**
Penn researchers created a hybrid light-matter particle (polariton) system that dramatically accelerates AI inference while consuming far less energy than silicon-based hardware. This matters for data teams running large-scale model inference, where energy cost and latency are growing operational constraints.
🔗 [Breakthroughs in AI Innovations for May 2026](https://www.aiandnews.com/blog/latest-ai-news-may-2026-3/)
━━━━━━━━━━━━━━━━━━━━━━━━
**5. 🛡️ Five Nations Release Agentic AI Security Guidance**
Cybersecurity agencies from the US, UK, Australia, Canada, and New Zealand jointly published guidance on "Careful Adoption of Agentic AI Services," covering risks like prompt injection, over-permissioned agents, and supply chain attacks. Software teams deploying AI agents in production should treat this as a practical security checklist before rollout.
🔗 [7 Explosive AI Updates in May 2026](https://imfounder.com/science-tech/ai/ai-updates-may-2026/)
━━━━━━━━━━━━━━━━━━━━━━━━
💡 *Stay ahead. Stay curious.*
For More: @kdnuggets @datasciencechats | 1 |
| 8 |  Sample PNG image | 1 |
| 9 |  Direct PNG file post @beingman | 1 |
| 10 | <b>GPT-5.5 Update</b>
Introducing GPT-5.5 — our smartest model yet, faster and built for complex tasks. Tap the button below to like this post.
For More: @kdnuggets @datasciencechats | 1 |
| 11 | <b>📰 KDnuggets Update</b>
<i>Google is expanding the Gemini 3 model family with the release of Gemini 3 Flash, which offers frontier intelligence built for speed at a fraction of the cost.</i>
🔗 Read more on the blog
For More: @kdnuggets @datasciencechats | 1 |
| 12 |  This is a 1x1 red pixel test image | 1 |
| 13 | <b>Welcome to Telegram Bot Automation! 🤖</b>
This is your first test post.
✨ Features:
• Supports text with HTML formatting
• Embeds images, videos, and documents
• Easy JSON-based content format
• Automated daily posting
<i>Generated by: Claude</i>
For More: @kdnuggets @datasciencechats | 1 |
| 14 | 🔬 *AI Research Digest*
📅 Week of May 24–May 30, 2026
━━━━━━━━━━━━━━━━━━━━━━━━
**1. 🤖 OpenClaw-RL — Train Any RL Agent Simply by Talking**
**Authors:** Gen-Verse (open-source org) | **arXiv:** 2603.10165
**Bottleneck solved:** Eliminates the need for manually defined reward functions in RL fine-tuning by intercepting live multi-turn conversations and using next-state signals as universal training feedback. Developers running self-hosted models via OpenClaw can now continuously fine-tune a personalized agent in the background — across terminal, GUI, SWE, and tool-call settings — without interrupting usage or writing a single reward function.
🔗 [OpenClaw-RL: Train Any Agent Simply by Talking](https://arxiv.org/abs/2603.10165)
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**2. 💰 Beyond the Context Window — Memory vs. Long-Context LLMs for Agents**
**Authors:** Independent researchers | **arXiv:** 2603.04814
**Bottleneck solved:** Quantifies the cost-performance tradeoff between stuffing full conversation history into long-context LLMs versus maintaining a structured fact-based memory store — directly addressing the spiraling inference cost of persistent agents. Data and ML teams building production agentic systems can use this analysis to decide when a RAG-style memory layer is cheaper and more accurate than paying per-token for a 1M-context window.
🔗 [Beyond the Context Window — arXiv](https://arxiv.org/abs/2603.04814)
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**3. ⚡ The 1/W Law — Context-Length Routing Beats GPU Upgrades for LLM Efficiency**
**Authors:** Infrastructure/systems researchers | **arXiv:** 2603.17280
**Bottleneck solved:** Shows that routing short and long context requests to separate GPU pools (two-pool topology) delivers ~2.5× better tokens-per-watt than a homogeneous H100 fleet — more gain than upgrading to B200s (~1.7×) — meaning smarter routing architecture is a bigger energy and cost lever than hardware. For teams running LLM inference at scale, this paper provides an analytical blueprint to cut infrastructure costs without waiting for the next chip generation.
🔗 [The 1/W Law — arXiv](https://arxiv.org/abs/2603.17280)
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💡 *Stay curious. Read the papers.*
For More: @kdnuggets @datasciencechats | 1 077 |
| 15 | 🤖 AI & Data Science Weekly Digest
Week of May 26–30, 2026
━━━━━━━━━━━━━━━━━━━━━━━━
1. 🔍 Google Gemini 3.5 Flash Goes Global at Google I/O
Google launched Gemini 3.5 Flash as the new default model for AI Search Mode — flagship-level intelligence at fast-inference speeds, now live in 200 countries across 98 languages, free with no subscription.
2. 🧠 Google Gemma 4 — Open Model, Closed-Model Performance
Gemma 4's 26B Mixture-of-Experts model activates only 3.8B parameters at inference time, outperforming models 20x its size on reasoning and agentic benchmarks.
3. 🗣️ xAI Drops Grok 4.3 with Voice Cloning & Agentic Modes
xAI released Grok 4.3 at aggressively low pricing, featuring a voice cloning suite and a dedicated Imagine creative agent mode for multimodal projects.
4. 💳 Ant Group Launches Agentic Commerce Trust Protocol
Alipay's parent company unveiled a full-stack AI payments infrastructure — including an AI Wallet and a Trust Protocol governing transactions executed autonomously by AI agents.
5. ⚠️ First Large-Scale Study Exposes Bias in Hiring Algorithms
Researchers published the first empirical large-scale study of hiring algorithms in the wild, uncovering systematic and concerning candidate rejection patterns across production systems.
━━━━━━━━━━━━━━━━━━━━━━━━
💡 Stay ahead. Stay curious.
For More: @kdnuggets @datasciencechats | 1 |
| 16 | 🤖 *AI & Data Science Weekly Digest*
📅 Week of May 24–May 30, 2026
━━━━━━━━━━━━━━━━━━━━━━━━
**1. 🚀 Google Gemini 3.5 Flash Launches at Google I/O — Now GA via API**
Google released Gemini 3.5 Flash as generally available on May 19, delivering frontier-level intelligence at 4x the speed of comparable models with pricing at $1.50/$9.00 per 1M tokens and model ID `gemini-3.5-flash`. Developers can use it in production today via the Gemini API in Google AI Studio — it's also now available as a model option in GitHub Copilot.
🔗 [Gemini 3.5: Frontier Intelligence with Action](https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-3-5/)
━━━━━━━━━━━━━━━━━━━━━━━━
**2. 🧠 Google Gemma 4 Released Open-Source Under Apache 2.0**
Google released the Gemma 4 family (2B, 4B, 26B MoE, 31B Dense) under an OSI-approved Apache 2.0 license — the first such release in the Gemmaverse — with 256K context windows, native vision and audio, and 140+ language support. The 31B model ranks #3 among all open models on the Arena AI leaderboard; teams can run it locally via Ollama or fine-tune freely on Hugging Face without licensing restrictions.
🔗 [Gemma 4: Byte for Byte, the Most Capable Open Models](https://blog.google/innovation-and-ai/technology/developers-tools/gemma-4/)
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**3. 🛠️ AMD EPYC "Venice" Becomes First HPC Chip in 2nm Production**
AMD announced that its 6th-gen EPYC processor "Venice" entered production ramp on TSMC's 2nm process on May 20 — the first high-performance computing product to reach this node — improving performance-per-watt and transistor density critical for AI data center workloads. Data and ML teams evaluating on-prem or cloud CPU infrastructure for agentic AI pipelines should track Venice availability as an increasingly competitive alternative to GPU-heavy deployments.
🔗 [AMD Announces Production Ramp of EPYC "Venice" on TSMC 2nm](https://www.amd.com/en/newsroom/press-releases/2026-5-20-amd-announces-production-ramp-of-next-generation-a.html)
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**4. 💳 OpenAI Opens Self-Serve ChatGPT Ads Manager with CPC Bidding**
OpenAI launched a beta self-serve Ads Manager on May 5, removing the previous $50,000 minimum spend and adding cost-per-click bidding — shifting ChatGPT from subscription-only toward an ad-supported platform. Developers building on the ChatGPT API or integrating it into products should review OpenAI's updated usage policies and consider how ad injection may affect response quality in production apps.
🔗 [New Ways to Buy ChatGPT Ads](https://openai.com/index/new-ways-to-buy-chatgpt-ads/)
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**5. 🔬 PolyU Completes First Full-Cycle Protein-Based Digital Data Storage**
Researchers at The Hong Kong Polytechnic University completed the first full read-write cycle using de novo engineered unnatural proteins to store and retrieve digital data, demonstrating high capacity, stability, and built-in encryption potential. This protein storage framework offers a long-term sustainable archival alternative as AI-generated data volumes scale beyond what silicon-based infrastructure can cost-effectively handle.
🔗 [PolyU Leads Breakthroughs in Protein-Based Data Storage](https://www.eurekalert.org/news-releases/1129790)
━━━━━━━━━━━━━━━━━━━━━━━━
💡 *Stay ahead. Stay curious.*
For More: @kdnuggets @datasciencechats | 1 |
| 17 | 🤖 AI & Data Science Weekly Digest
Week of May 26–30, 2026
━━━━━━━━━━━━━━━━━━━━━━━━
1. 🔍 Google Gemini 3.5 Flash Goes Global at Google I/O
Google launched Gemini 3.5 Flash as the new default model for AI Search Mode — flagship-level intelligence at fast-inference speeds, now live in 200 countries across 98 languages, free with no subscription.
2. 🧠 Google Gemma 4 — Open Model, Closed-Model Performance
Gemma 4's 26B Mixture-of-Experts model activates only 3.8B parameters at inference time, outperforming models 20x its size on reasoning and agentic benchmarks.
3. 🗣️ xAI Drops Grok 4.3 with Voice Cloning & Agentic Modes
xAI released Grok 4.3 at aggressively low pricing, featuring a voice cloning suite and a dedicated Imagine creative agent mode for multimodal projects.
4. 💳 Ant Group Launches Agentic Commerce Trust Protocol
Alipay's parent company unveiled a full-stack AI payments infrastructure — including an AI Wallet and a Trust Protocol governing transactions executed autonomously by AI agents.
5. ⚠️ First Large-Scale Study Exposes Bias in Hiring Algorithms
Researchers published the first empirical large-scale study of hiring algorithms in the wild, uncovering systematic and concerning candidate rejection patterns across production systems.
━━━━━━━━━━━━━━━━━━━━━━━━
💡 Stay ahead. Stay curious.
For More: @kdnuggets @datasciencechats | 1 226 |
| 18 | This is a 1x1 red pixel test image | 1 |
| 19 | This is a 1x1 red pixel test image | 1 |
| 20 | <b>Welcome to Telegram Bot Automation! 🤖</b>
This is your first test post.
✨ Features:
• Supports text with HTML formatting
• Embeds images, videos, and documents
• Easy JSON-based content format
• Automated daily posting
<i>Generated by: Claude</i> | 1 |
