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23 articles found

LangExtract: How Google Brought NLP Back

NLP

Featured

LangExtract: How Google Brought NLP Back

Traditional NLP tools failed. LangExtract is Google's bet to fix enterprise NLP extraction once and for all.

#NLP#LLM#Google

Unsloth

Unsloth Flex Attention: Breaking NVIDIA's VRAM Cartel With 60K Context Windows

How a new attention mechanism enables 8x longer context lengths while cutting VRAM requirements in half for LLM training on consumer hardware.

#Unsloth#LLM#Fine-tuning

AI writing

Kimi K2-0905 Just Outscored Humans in Creative Storytelling (And That Changes Everything)

The Kimi K2-0905 model's narrative precision has shattered creative writing benchmarks, forcing us to confront whether AI has crossed the threshold into genuine artistry.

#AI writing#creative writing#LLM

local-llm

Qwen Next Just Made Every Other Local LLM Look Obsolete

Alibaba's hybrid MoE architecture delivers 80B parameter performance with 3B activation costs, revolutionizing local task automation

#local-llm#llm#moe...

Swiss Army Knife or Swiss Cheese? Apertus Promises 1,500 Languages But Delivers Mostly English

Switzerland's 'fully transparent' Apertus LLM claims 1,500 language support, but the reality of multilingual AI reveals uncomfortable truths about European AI independence.

#ai#open-source#llm

llm

We Accidentally Trained AI to Lie to Us

OpenAI's new confidence-targeted evaluation method reveals we've been rewarding LLMs for confident bullshit instead of honest uncertainty

#llm#hallucination#ai-evaluation...

LLM

Why SQL Just Killed Vector Databases for LLM Memory (And Why Everyone's Lying About It)

Developers are abandoning vector databases for LLM memory, not because they're broken, but because they're fundamentally misaligned with how memory actually works in real-world agents. Meet the SQL-first approach that's rewriting the rules.

#LLM#memory#SQL...

llm

Your LLM Integration Architecture Is Probably Wrong

Why most teams build LLM systems that fail at scale, and the architectural patterns that actually work

#llm#architecture#software-design...

95% 'Accuracy' Is Poison: The Danger of Trusting AI Agents With Business Intelligence

Enterprises replacing BI teams with AI agents are gambling with statistical Russian roulette, 95% accuracy means 1 in 20 decisions are based on hallucinations.

#ai#business-intelligence#llm...

The Great AI Disillusionment: When Hype Meets Hard Reality

Why early AI adopters are losing faith in large language models as reliability gaps, unpredictable failures, and real-world costs expose the cracks in the revolution

#ai#llm#reliability...

llm

Browsers Ditching Your Privacy Was Never Cool, So IBM Ditched Them Instead

IBM's Granite 4.0 Nano loads smarter AI onto your laptop, phone, or potato PC, banishing the cloud to the bargain bin of bad ideas.

#llm#on-device-ai#webgpu...

llm

When Less Is Actually More: Cerebras' REAP Exposes Expert Merging as Flawed MoE Strategy

REAP pruning outperforms merging in MoE models, enabling near-lossless compression of 480B giants to local hardware

#llm#moe#compression...

ai-generated-code

Comprehension Debt: The Architectural Time Bomb in Your AI-Generated Codebase

As LLMs spew unread code into production, teams face a new kind of technical debt where systems work but no human understands them.

#ai-generated-code#technical-debt#software-architecture...

CPU-First AI: BitDistill Enables High-Performance LLMs Without GPUs

With 2.65x faster CPU inference, BitDistill signals a potential shift toward CPU-efficient AI deployment, reducing reliance on expensive GPU infrastructure.

#ai#llm#cpu-inference...

llm

GLM-4.6-GGUF: The Hardware-Breaking LLM That's Actually Worth It

Z.ai's latest model pushes boundaries with 200K context and 15% efficiency gains, but can your rig handle the 204GB quant?

#llm#ai#machine-learning...

Granite 4.0: The End of Cloud AI Dominance?

IBM's new language models challenge the status quo with radical efficiency gains and browser-based execution

#ai#llm#ibm...

llm

Karpathy's NanoChat Shows Why $100 Beats Enterprise Chatbots

How Andrej Karpathy's minimalist codebase demolishes bloated LLM infrastructure with brutal efficiency.

#llm#ai#architecture...

llm

Linear Attention's Revenge: How Kimi Delta Attention Smashes the KV Cache Bottleneck

Moonshot AI's hybrid architecture delivers 6x decoding speed with 75% less memory, making 1M-token contexts actually practical.

#llm#attention-mechanisms#efficiency...

edge-ai

Meta's MobileLLM-Pro: The 1B Parameter Heavyweight That's Punching Above Its Weight Class

Meta's new 1B foundational model outperforms Gemma and Llama benchmarks while fitting in your pocket. But is distilled intelligence the future?

#edge-ai#llm#edge-computing...

computer-vision

Your Document AI Pipeline is Broken and Nanonets-OCR2 Just Called It Out

The open-source vision model that's exposing how bad traditional OCR actually is at preparing documents for LLMs

#computer-vision#document-processing#open-source...

llm

Training AI on Internet Trash is Giving LLMs Permanent Brain Damage

New research reveals junk social media data causes lasting cognitive decline in AI models, with irreversible damage to reasoning and personality.

#llm#ai-safety#machine-learning...

Why Your AI Assistant Needs a Bad Attitude

Microsoft's UserLM-8b flips the script by training AI to think like messy, inconsistent humans instead of perfect assistants.

#AI#UserLM#Microsoft...

rag

Your RAG System is Lying to You: The Uncomfortable Truth About Production Metrics

When high-stakes RAG deployments fail silently, teams discover that traditional accuracy metrics miss everything that matters

#rag#evaluation#production...

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