AGI Dreams -- Archive
Complete archive of AI news digests
All Episodes
- The Invisible Attack Surface — When CSS and Memory Become Weapons -- 2026-02-18
- The Open-Weight Arms Race Heats Up -- 2026-02-17
- Context Drift — When Patience Becomes an Exploit -- 2026-02-16
- Local AI Development Implementation -- 2026-02-13
- Claude Opus 46 Safety and Capabilities Assessment -- 2026-02-12
- Local LLM Infrastructure and Optimization -- 2026-02-11
- Claude Code Evolution and Advanced Patterns -- 2026-02-10
- AI Security and Governance Challenges -- 2026-02-09
- AI Security Vulnerabilities and Exploits -- 2026-02-06
- AI Security and Safety Concerns -- 2026-02-05
- Agentic Coding Infrastructure and Tools -- 2026-02-04
- AI-Assisted Development Tools and Workflows -- 2026-02-03
- AI Security Vulnerabilities and Threats -- 2026-02-02
- Local AI Infrastructure and Optimization -- 2026-01-30
- AI Development Tools and Infrastructure -- 2026-01-29
- AI Development Infrastructure and Optimization -- 2026-01-28
- Local LLM Infrastructure and Resource Optimization -- 2026-01-27
- Local AI Infrastructure and Sovereignty -- 2026-01-26
- AI Security and Safety Frameworks -- 2026-01-23
- AI Security and Safety Concerns -- 2026-01-22
- AI Agent Security and Trust Infrastructure -- 2026-01-21
- Local AI Infrastructure and Model Management -- 2026-01-20
- AI Agent Development and Automation -- 2026-01-19
- AI Security Vulnerabilities and Attack Vectors -- 2026-01-16
- AI Security and Infrastructure Vulnerabilities -- 2026-01-15
- Open-Weight Model Releases and Architectures -- 2026-01-14
- Open-Weight AI Model Releases and Performance -- 2026-01-13
- Local LLM Performance and Optimization -- 2026-01-12
- AI Agent Development Tools and Frameworks -- 2026-01-09
- Local AI Infrastructure and Deployment -- 2026-01-08
- Open-Weight Model Releases and Frameworks -- 2026-01-07
- Local LLM Performance Infrastructure -- 2026-01-06
- Open-Weight Model Releases and Performance -- 2026-01-05
- AI Agent Development and Runtime Systems -- 2026-01-02
- Open-Weight Model Releases and Multimodal AI -- 2025-12-31
- Local LLM Performance and Optimization -- 2025-12-30
- Local LLM Development and Tools -- 2025-12-29
- AI Safety and Security Vulnerabilities -- 2025-12-23
- Open-Weight Model Releases and Performance -- 2025-12-22
- Open-Weight Model Releases and Development -- 2025-12-19
- Local LLM Development and Deployment -- 2025-12-18
- NVIDIA Nemotron 3 Model Release and Evaluation -- 2025-12-17
- AI Agent Frameworks and Autonomy -- 2025-12-16
- Local LLM Infrastructure and Deployment -- 2025-12-15
- Privacy Meets Production: Local AI Tradeoffs -- 2025-12-12
- Transformer Authors New Model Sparks Debate -- 2025-12-11
- LLM-as-Judge Falls to Confident Idiot Problem -- 2025-12-10
- Local RAG Gets Simpler With MCP -- 2025-12-09
- Smarter Memory for Giant AI Models -- 2025-12-08
- GPU Ownership vs API Costs: The Hidden Math -- 2025-12-05
- Abliterated Models: Norm-Preserving Guardrail Removal -- 2025-12-04
- Small Orchestrator Model Outperforms GPT-5 -- 2025-12-03
- GPU Showdown: Single Card vs Multi-GPU -- 2025-12-02
- Consumer GPUs Master FP8 Training -- 2025-12-01
- AMD Strix Halo Cluster Benchmarks -- 2025-11-28
- Custom Quantization Beats Pre-Built Models -- 2025-11-26
- Vulkans Uphill Battle Against CUDA Dominance -- 2025-11-25
- Privacy Hardware and the Local Stack -- 2025-11-24
- Local multimodal systems and compression -- 2025-11-21
- VRAM math goes mainstream: Tool calling finally behaves -- 2025-11-20
- Scale-out not cold starts: AI infra under attack better telemetry -- 2025-11-19
- Consumer PCIe reality check: When prompts become pulpits -- 2025-11-18
- Halftrillion runs at home: ShadowMQ and layered defenses -- 2025-11-17
- Encrypted chats still leak topics -- 2025-11-14
- Local LLM engineering gets sharper -- 2025-11-13
- Sharper vision through focus: Local runners get management layers -- 2025-11-12
- Agent guardrails move forward: Offensive testing meets hardening -- 2025-11-11
- Kubernetes stacks meet RAG reality -- 2025-11-10
- Fine-tuning giants locally: Open agents and research stacks -- 2025-11-07
- Vision models: quirks and fixes -- 2025-11-06
- Agent skills memory autonomy: Coordinating agents at scale -- 2025-11-05
- Agent frameworks go local-first -- 2025-11-04
- Local AI stacks meet reality: Efficient diffusion on AMD GPUs -- 2025-11-03
- Multimodal memory and perception -- 2025-11-02
- Faster loading leaner infra: DIY GPU rigs vs racks -- 2025-11-01
- Ontologies and procedural memory rise -- 2025-10-31
- Cloud privacy interception realities -- 2025-10-30
- Local models nail structure: Agents without the mystery box -- 2025-10-29
- Edge GPUs go realtime: Open models chase coding wins -- 2025-10-28
- Vision compression meets real datasets -- 2025-10-27
- Document intelligence moves beyond OCR -- 2025-10-26
- Qwen lands in llamacpp: MoE trade-offs and pruning realities -- 2025-10-25
- GPU ecosystems in flux: AI security: frameworks and browsers -- 2025-10-24
- RL training meets ops reality: Lighter multiagent heavier orchestration -- 2025-10-23
- Phones inch toward real local AI -- 2025-10-22
- Alwayson agents measured: GUI agents learn precision -- 2025-10-21
- Local-first AI goes practical: Agent plumbing with MCP bridges -- 2025-10-20
- Nanochat makes LLMs tangible: Routing across many models -- 2025-10-19
- Local GPUs hit real limits: Multimodal speech: promise potholes -- 2025-10-18
- AI landscape shifts competition sharpens -- 2025-10-17
- Memory hints and retrieval help small models reason -- 2025-10-16
- Lowprecision training hits stride -- 2025-10-15
- Cooperative prompts reshape alignment -- 2025-10-14
- Agents ship backends not certainty -- 2025-10-13
- Local coding LLMs on Apple Silicon -- 2025-10-12
- AMD-first LLM inference push: Tiny models big retrieval gains -- 2025-10-11
- Local multimodal catches up: Throughput MoE and templating -- 2025-10-10
- On-device models hit stride: Agentic tooling and MCP data -- 2025-10-09
- Browser LLMs go truly local: Local speech-to-speech matures -- 2025-10-08
- Legal LLMs reasoning and thinking -- 2025-10-07
- Local GPUs stretch their legs: Caches meet long contexts -- 2025-10-06
- Fine-tuning VRAM myths tested: Agents APIs and testing tools -- 2025-10-05
- Blackwell FP4 reality check: Local models now mobile -- 2025-10-04
- Reasoning wins benchmarks wobble -- 2025-10-03
- Local models at 32GB scale: Terminal agents minimal orchestration -- 2025-10-02
- Efficient LLMs and Attention Tradeoffs -- 2025-10-01
- Small Models Big Data Real Returns -- 2025-09-30
- MoE Models and Local Inference Tradeoffs -- 2025-09-29
- LLM Access Trust and Integrity Debates -- 2025-09-28
- Local LLM Hardware Bottlenecks and Workarounds -- 2025-09-27
- Open-Source LLMs Copyright and New Architectures -- 2025-09-26
- Community-Driven LLM Vulnerabilities Outpace Red Teams -- 2025-09-25
- Dual RTX Pro 6000 on PCIe x8: Myths Bottlenecks and Real-World Performance -- 2025-09-24
- H100 vs RTX 6000 PRO: The LLM Showdown -- 2025-09-23
- Self-hosted AI Interfaces Advancing -- 2025-09-22
- Local LLMs: Performance Workflows and Optimization -- 2025-09-21
- AI Model Security Safety and Trust Scoring -- 2025-09-20
- Big Models Bigger Benchmarks: Qwen3-Nexts Leap Forward -- 2025-09-19
- Model Management Cross-GPU Challenges and Performance Tweaks -- 2025-09-18
- Enterprise RAG Revolution: AI NPCs Enter Gaming -- 2025-09-17
- Local LLM Revolution on Mobile: AI Agents Beat Tech Giants -- 2025-09-16
- Performance Breakthroughs and Bottlenecks -- 2025-09-15
- Mega-Efficient AI Models Emerge -- 2025-09-14
- Hardware for Affordable LLM Inference -- 2025-09-12
- Big leaps in local and enterprise AI inference -- 2025-09-10
- Renting beats buying for most: Open models for languages and the edge -- 2025-09-09
- Hybrid LLM Reasoning Tokenization and Deep Recursion -- 2025-09-08
- Language Translation Model Advances and Challenges -- 2025-09-07
- Advances in Local Private and Efficient Edge AI -- 2025-09-06
- Foundation Models Evolve: Voice Language Image -- 2025-09-05
- LLMs Coding and Local Deployment Advice -- 2025-09-04
- Next-Gen Retrieval: GraphRAG Minimalist RAG and Knowledge Visualization -- 2025-09-03
- MoE Architecture Debates and Pragmatic Choices -- 2025-09-02
- Fine-tuning for Fun and Function -- 2025-09-01
- VLM Benchmark Realities: Social Reasoning and Local Agents -- 2025-08-31
- Microcontroller LLMs Break Size Barriers -- 2025-08-30
- LLM Performance Breakthroughs: Audio Generation Revolution -- 2025-08-29
- Local Language Model Innovations and Benchmarks -- 2025-08-28
- Local AI Hardware Scaling Dilemma -- 2025-08-27
- Hardware tradeoffs for local AI inference -- 2025-08-26
- Expanding Code AI: Qwen-Code Agentic Ecosystems -- 2025-08-25
- State-of-the-Art Reasoning Model Showdowns -- 2025-08-24
- Practical Acceleration in LLM and AI Pipelines -- 2025-08-23
- Local LLM Inference Breakthroughs -- 2025-08-22
- Local AI Ecosystem Thrives with New Tools -- 2025-08-21
- Breakthrough Model Releases: Model Optimization Advances -- 2025-08-20
- wrench: ROCm Performance Claims Scrutinized -- 2025-08-19
- LocalAI Modernizes Modular Backends -- 2025-08-18
- Hardware Limits for Local Models -- 2025-08-17
- Hardware Compatibility Challenges -- 2025-08-16
- Video Processing Advances: Local Inference Breakthroughs -- 2025-08-15
- computer: LLM Performance Optimization -- 2025-08-14
- Local AI Infrastructure Evolution -- 2025-08-13
- Local Models Break Performance Barriers -- 2025-08-12
- Local AI Models Push Accessibility -- 2025-08-11
- AMD ROCm7 Boosts Local AI: New Models Optimization Advances -- 2025-08-10
- Security Concerns Spotlighted: Agent Ecosystem Expands Rapidly -- 2025-08-09
- Small models big gains: Training at scale faster -- 2025-08-08
- Open Models and the New LLM Landscape -- 2025-08-07
- Agentic Coding Assistants and Local Autonomy -- 2025-08-06
- Local Model Breakthroughs: GLM-45 Air and Qwen3-30B -- 2025-08-05
- Open Models Local Tools and the New AI Stack -- 2025-08-04
- Hierarchical Reasoning: A Leap Beyond CoT -- 2025-08-03
- Hardware Choices Shape Local AI Workflows -- 2025-08-02
- Qwen3 Models Push Local AI Forward -- 2025-08-01
- Modern LLMs: Under the Hood: Open Efficient MoE Models Dominate -- 2025-07-31
- LLM Inference: Enterprise vs Home -- 2025-07-30
- Community-Driven LLM Security: New Findings -- 2025-07-29
- Open Models Challenge Closed Giants -- 2025-07-28
- Security Safety and LLM Vulnerabilities -- 2025-07-27
- Real-World Table Intelligence: Challenges and Progress -- 2025-07-26
- Qwen3-235B Advances GPT-5 Teasers and LLM Reasoning Progress -- 2025-07-25
- Adaptive Retrieval and RAG for Developer LLMs -- 2025-07-24
- Small Models Big Reasoning Gains -- 2025-07-23
- Local LLMs: Hardware Models and Practical Tradeoffs -- 2025-07-22
- Language Models and Reasoning in Focus -- 2025-07-21
- Hardware Realities for Massive LLMs -- 2025-07-20
- Argument Mining: LLMs Benchmarks and Pitfalls -- 2025-07-19
- Linear Attention Breakthroughs in Image Generation -- 2025-07-18
- Encoder-Decoders Fair Model Comparisons and the T5Gemma Debate -- 2025-07-17
- Local LLM Hardware: 5K to 25K Rigs Compared -- 2025-07-16
- Hardware Bottlenecks and LLM Inference -- 2025-07-15
- OpenAIs Open Model and the Reasoning Race -- 2025-07-14
- AI4Research: Mapping the State of AI Science -- 2025-07-13
- Open Source Model Distribution at a Crossroads -- 2025-07-12
- Local AI Agents and Privacy-First Productivity Tools -- 2025-07-11
- Hardware Model Selection and Local LLMs -- 2025-07-10
- Hardware and Model Speed: Why Commercial LLMs Are So Fast -- 2025-07-09
- Model Size Performance and Local LLM Choices -- 2025-07-08
- Multi-LLM Coding Workflows Emerge -- 2025-07-07
- Local LLMs: Continuity Privacy and Usefulness -- 2025-07-06
- Open-Source LLMs: Local Coding Model Formats and Tooling -- 2025-07-05
- Kyutai TTS Redefines Real-Time Voice AI -- 2025-07-04
- Local LLM Launchers and Tooling Advances -- 2025-07-03
- Consumer Hardware for Local LLMs -- 2025-07-02
- 🖥️ Local LLMs: Quantization, Hardware, and Usability -- 2025-07-01
- 🧑💻 Small Models, Big Surprises: Jan-nano and MCP -- 2025-06-30
- 🧑💻 Small LLMs Find Real-World Utility -- 2025-06-29
- 🖥️ Local Model Management Tools Simplify AI Workflows -- 2025-06-28
- 🧑💻 Ollama, RAG, and the Local LLM Ecosystem -- 2025-06-27
- 🧠 DeepSeek R1 Surpasses Expectations in Benchmarks -- 2025-06-26
- 🐕 Shisa V2 405B: Japan's LLM Milestone -- 2025-06-25
- 🧑💻 Open-Source AI Agents Advance on SWE-bench -- 2025-06-24
- 🧑💻 Model Context Protocol: Real-World Adoption and Security Moves -- 2025-06-23
- 🧑💻 Local, Private LLM Workflows Advance -- 2025-06-22
- 🧠 Autonomous AI Agents Get Smarter -- 2025-06-21
- 🖥️ Local AI Speech: Speed & Accuracy Leap -- 2025-06-20
- 🖥️ Open-Source LLMs: Hardware, Performance, Frustrations -- 2025-06-19
- 🖥️ Progress in Local LLMs: Speed, Context, Vision -- 2025-06-18
- 🧑💻 DeepSeek R1 Sets New Benchmark -- 2025-06-17
- 🖥️ PCIe Bandwidth: Key to Fast Inference -- 2025-06-16
- 🧮 Dataset Deduplication Speeds Up LLMs -- 2025-06-15
- 🧠 Progress in LLM Reasoning and Quantization -- 2025-06-14
- 🖥️ Budget AI Hardware: AMD, Nvidia, Apple -- 2025-06-13
- 🧑💻 Qwen 2 -- 2025-06-12
- 🤖 System Prompt Learning Boosts Local LLMs -- 2025-06-11
- 🧑💻 Open Models Narrow AI Gap -- 2025-06-10
- 🧩 Embedding Engines: Same Model, Divergent Results -- 2025-06-09
- 🧑💻 Open Source Models Rival SOTA Video -- 2025-06-08
- 🖥️ Local LLMs: DIY at Every Scale -- 2025-06-07
- 🖥️ Desktop AI Tools Get Lighter, Smarter -- 2025-06-06
- 🖥️ Local LLM Hardware: Bottlenecks, Scaling, Choices -- 2025-06-05
- 🧑💻 Local AI on Phones: Privacy, Power, Progress -- 2025-06-04
- 🖥️ GPU Choices for Local AI Enthusiasts -- 2025-06-03
- 🧑💻 Autonomous Novel Writing Gets Smarter -- 2025-06-02
- 🖥️ Local AI: Hardware, Cost, and Privacy Calculus -- 2025-06-01
- 🧑💻 Math Reasoning Models Get Cheaper, Smarter -- 2025-05-31
- 🧑💻 Advances in Local and Open Source LLMs -- 2025-05-30
- 🖥️ Local LLM Hardware Choices Compared -- 2025-05-29
- 🖥️ Local Model Deployment Simplified -- 2025-05-28