Category
LLM & Language Models
How LLMs work, honest comparisons, and production usage
// 12 articles filed
// FIG. CAT-LLM
PristrenPristrenHow LLMs work, honest comparisons, and production usage
// 12 articles filed
Microsoft's Phi-3 family delivers surprising capability from tiny parameter counts. Phi-3 Mini at 3.8B parameters runs in 4GB of VRAM with MMLU scores that embarrass models three times its size. Practical deployment guide with benchmarks and honest tradeoffs.
Mahmudul Haque Qudrati
CEO & ML Engineer
Function calling gives LLMs a structured way to request execution of specific functions with typed parameters, eliminating the need to parse free-form text outputs.
Mahmudul Haque Qudrati
CEO & ML Engineer
Claude 3.5 Sonnet leads SWE-Bench with 49% resolved. GPT-4o scores 90.2% on HumanEval. Deepseek V3 matches GPT-4o at 20x lower cost. Here is the full breakdown.
Mahmudul Haque Qudrati
CEO & ML Engineer
Temperature 0 gives deterministic output. Temperature 1.0 adds variety. Above 1.0, output degrades. Here is what temperature, top-p, and top-k actually control.
Mahmudul Haque Qudrati
CEO & ML Engineer
The most common fine-tuning mistake is using it to inject knowledge. Fine-tuning changes style and behavior, not what the model knows. Prompting should always come first.
Mahmudul Haque Qudrati
CEO & ML Engineer
Deepseek trained a GPT-4o-competitive model for a reported $5.6M - roughly 1/20th of comparable frontier model training costs - and released it under MIT license.
Mahmudul Haque Qudrati
CEO & ML Engineer
Embeddings convert text into dense numerical vectors that capture semantic meaning, enabling similarity search and retrieval at scale without running inference on every query.
Mahmudul Haque Qudrati
CEO & ML Engineer
GPT-4o leads on tool use and multimodal tasks. Claude 3.5 Sonnet leads on coding, long documents, and instruction following. Here is the full benchmark breakdown for 2026.
Mahmudul Haque Qudrati
CEO & ML Engineer
Deepseek V3 was trained for $5.6M and matches GPT-4o on most benchmarks. At 20-30x lower cost, it changes the economics of building AI products.
Mahmudul Haque Qudrati
CEO & ML Engineer
A plain-English guide to how LLMs actually work: tokens, attention, training vs inference, why they hallucinate, and what context windows mean for your workflow.
Mahmudul Haque Qudrati
CEO & ML Engineer
Real benchmark scores, exact pricing, and honest assessments of what GPT-4o, Claude 3.5 Sonnet, Gemini 1.5 Pro, and Deepseek V3 are genuinely best at in 2026.
Mahmudul Haque Qudrati
CEO & ML Engineer
A token is not a word. It is a text chunk of 1-4 characters. Understanding tokens directly reduces your API costs and improves how you structure prompts.
Mahmudul Haque Qudrati
CEO & ML Engineer
Deep dives into ML algorithms, models, and applications
AI trends, techniques, and real-world implementations
Every technique that works — with real examples
Claude Code, Cursor, Copilot, open-source tools reviewed honestly
Local LLMs, open models, free AI infrastructure
Fewer tokens, cheaper APIs, local alternatives with real numbers
Benchmarks explained, evaluation frameworks, model testing
LLM SEO, AI SEO, Google AI Overviews, developer marketing
iOS, Android, and cross-platform mobile app development
Modern web technologies, frameworks, and best practices
Data analysis, visualization, and engineering insights
Autonomous agents, LLM applications, and intelligent systems