While Large Language Models (LLMs) operate strictly on textual inputs,Vision-Language Models (VLMs) extend this capability by integrating visual encoders with language models to achieve joint cross-modal understanding of both imagery and text.VLMs have bec...
If you’ve been building with Large Language Models (LLMs),you’re likely familiar with Prompt Engineering.You type a prompt,evaluate the response,tweak your wording,and send it back.It’s effective,but it has a glaring bottleneck: You.As AI system archite...
Combining Milvus,an open-source vector database,with Large Language Models (LLMs) is not only practical but has become a prevalent and highly effective strategy for building advanced AI applications.The core idea is to leverage Milvus's ability to store,in...
What is TensorRT?TensorRT is an NVIDIA SDK (Software Development Kit) designed for high-performance deep learning inference.It includes an optimizer and runtime that takes trained neural networks and optimizes them for faster execution on NVIDIA GPUs.Tenso...
Model Context Protocol (MCP) is a framework that enables LLMs (Large Language Models) to seamlessly interact with external tools and data sources,effectively extending their capabilities beyond their pre-trained knowledge.It defines a standardized way for ...
xAI,Elon Musk's artificial intelligence company,was founded in March 2023.Its stated goal is to understand the true nature of the universe,a significant departure from the more commercially focused aims of many other AI companies.While its history is short...
A fleet of a million vehicles drives a million hours today.Tomorrow it does it again.Somewhere in there are the forty seconds that would fix your model.The hard part was never the training job.It's that 99.999% of what the fleet sees is a car following a c...
Your model fails at 2 a.m.on a rainy street.You have the clip.You have the logs.You even have the exact frame where confidence collapsed.Now what?.For most teams,the answer is a week of Slack threads,a half-remembered S3 prefix,and someone scrubbing throug...
To transition a PyTorch deep learning object detection model from a cloud GPU running at 15 FPS to a vehicle's onboard automotive ECU requiring over 40 FPS within a limited thermal and power budget,the most effective optimization strategy involves applying...
Designing a robust system infrastructure for allocating GPU and LLM clusters requires an optimized task management approach to address severe resource limitations.Because these computational clusters operate under strict hardware constraints,the infrastruc...
Bridging the gap between Machine Learning (ML) theory and infrastructure often comes down to shift in perspective: ML is the intelligence (the brain),and Infrastructure is the system that keeps it alive,fed,and useful to the world (the body and environment...
To build a chatbot using Microsoft's AutoGen framework that can automatically write and execute Python code based on your chat prompt,you can use the autogen library. In AutoGen,the standard setup involves two main agents:An AssistantAgent that acts as the...
The paradigm shift in building applications with Large Language Models (LLMs) has moved from simple,single-prompt interactions to complex,multi-agent systems that require memory,decision-making loops,and collaboration.To address this,the creators of LangCh...
Microsoft AutoGen is an open-source framework designed to simplify the development of advanced Large Language Model (LLM) applications.Its core paradigm relies on multi-agent conversation,where multiple specialized agents communicate,collaborate,and orches...
What is AV ML?Autonomous Vehicle (AV): Refers to self-driving cars or vehicles capable of perceiving their environment and operating without human input.The ultimate goal of AVs is to enhance safety,efficiency,and accessibility in transportation.Machine Le...
You are contemplating purchasing a MacBook Pro primarily for LLM development.Your core consideration is whether to opt for a cost-effective,used M1 or M2 MacBook Pro with 64GB of unified memory,rather than waiting for or investing in a new M4 model.Your ra...
The core mission is to develop kernel-level implementations for a variety of Deep Neural Network (DNN) models,specifically targeting Arm architectures.The primary goals are to optimize these implementations for maximum power efficiency and performance,cruc...
While Large Language Models (LLMs) have undeniably transformed AI capabilities across numerous tasks,they do not diminish the critical need for direct deep learning implementation using frameworks such as PyTorch,TensorFlow,or JAX.LLMs are powerful general...
LLMs,also known as AI Foundation Models,deliver excellent performance independently,yet their information regarding specific domains is frequently outdated or inaccurate.To develop a ChatGPT specialized for a particular field,a strategy is required that in...
When you use Claude via Bedrock: it has a prompt size limit,typically around 5,000 bytes for some models (Claude 1 / 2).Exceeding that triggers errors.Here’s how you can handle it: .1.Chunking / Splitting the InputBreak your large prompt into smaller pi...
One of the rising area regarding smart search is to use Vector Database stored in S3 with Amazon Bedrock so you can use it for retrieval-augmented generation (RAG) or semantic search.Amazon Bedrock is a fully managed service that allows developers to acces...
Model Context Protocol (MCP)The Model Context Protocol (MCP) is a conceptual framework or specification designed to standardize the interaction between client applications and machine learning (ML) models.Its primary goal is to provide a consistent and ric...
Both SLMs (Small Language Models) and LLMs (Large Language Models) are types of language models,but they differ primarily in size (number of parameters) and consequently,in their capabilities and scope.LLMs,with their massive parameter counts,possess a wid...
Below is from Aurimas Griciūnas showing hierarchical layers for AI Agents.Sometimes 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀 might seem simple from the outside.They are not 👇There are many moving pieces that production ready Agentic Systems rely on. I like to split the 𝗛𝗶𝗲𝗿...
What is MCP?Model Context Protocol (MCP) is a framework,often used in fields like Model-Based Systems Engineering (MBSE),but increasingly relevant in AI and software development in general,that defines how models (of systems,data,processes,etc.) should be ...
Recently,many generative AI models have emerged,broadening the range of choices.Personally,I find Gemini to be more user-friendly and am therefore following its development closely.However,other companies' solutions are also rapidly improving their functio...
gRPC is a high-performance,open-source universal RPC (Remote Procedure Call) framework developed by Google and initially released in 2015.Its history traces back to Google's internal needs for efficient communication between services,evolving from their in...
The ad exchange engine calls external DSPs,ad networks,and third-party APIs synchronously during the bidding phase.When a downstream service degrades—whether due to latency spikes,temporary outages,or cascading failures—the ad engine can exhaust thread p...
A significant shift is underway within the foundational layers of technology,where major engineering teams are increasingly turning to Rust,a systems programming language.This adoption signals a quiet revolution focused on eliminating entire classes of bug...
What is Milvus?Milvus is an open-source vector database designed for storing,indexing,and managing billions of embedding vectors.It specializes in high-performance similarity search over these vectors.Milvus is built to handle the unique challenges of vect...