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The next generation of billion-dollar companies won’t be built in glass offices, with huge teams, layers of management, and complex org charts. They will be built by 5 people and AI. This isn’t a slogan.
7+ min ago (81+ words) [jaideepparashar] Why the Next Unicorns Will Be Built With 5 People and AI Jaideep Parashar " Nov 25 #ai #productivity #performance #devops Templates let you quickly answer FAQs or store snippets for re-use. - Work Director ReThynk AI Innovation & Research Pvt Ltd "The Hidden Cost of AI Hype in Developer Communities." Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink. Hide child comments as well...
ESP32-S3 + TensorFlow Lite Micro: A Practical Guide to Local Wake Word & Edge AI Inference
7+ min ago (196+ words) This post breaks down how we deploy TensorFlow Lite Micro (TFLM) on ESP32-S3 to run real-time wake word detection and other edge-AI workloads. If you're exploring embedded ML on MCUs, this is a practical reference. ESP32-S3 brings a useful combination of: It's powerful enough to run quantized CNNs for audio, IMU, and multimodal workloads while staying power-efficient. ESP-DSP supports optimized FFT, DCT, and filtering primitives. 2. Feature extraction (MFCC) MFCC remains the standard for low-power speech workloads: On ESP32-S3, MFCC extraction typically takes 23 ms per frame. 3. Compact CNN model Model size after int8 quantization: 100300 KB. Convert & quantize: 4. Deployment to MCU Convert .tflite " C array: Load + run with TensorFlow Lite Micro: Because the workflow is generalizable, simply swapping the model unlocks new tasks: Environmental sound classification Glass break, alarm, pet sound detection (812 FPS depending on model) Vibration & anomaly detection Predictive maintenance for pumps, motors, or fans....
USAN Achieves the Amazon Web Services (AWS) Generative AI Competency
19+ min ago (188+ words) SysAid Announces Major Enhancements to Its AI Agent Builder, Introducing Fully Agentic Coding Multichain AI-NFT Platform Colle AI (COLLE) Deploys Autonomous Blueprint Engine for Instant Asset Structuring "Achieving the AWS Generative AI Competency underscores that USAN is equipped to help enterprises apply AI in successful, high-return projects," said Farid Shenassa, Chief Technology Officer at USAN. "Using AWS, we are driving better customer experiences, richer insights, and more efficient operations." The AWS Competency Program aims to assist customers in connecting with AWS Partners who possess extensive knowledge and technical expertise in using AWS technologies and best practices to adopt generative AI. These AWS Partners facilitate the seamless integration and deployment of AWS-based solutions to meet the unique needs of all customers, from startups to global enterprises. "Generative AI represents a new era in customer experience," said Matthew Storm, CX Evangelist at…...
Microsoft’s Fara-7B: New agentic LLM from screenshots
21+ min ago (837+ words) [Microsoft's Fara-7B: New agentic LLM from screenshots]Microsoft Research released Fara-7B, a 7-billion-parameter agentic small language model for computer use, capable of executing tasks locally from screenshots. Fara-7B functions as an open-weight Computer Use Agent, predicting mouse and keyboard actions directly from screenshots. Its compact size allows execution on a single user device, which reduces latency and retains browsing data locally. Unlike [] [Microsoft's Fara-7B: New agentic LLM from screenshots]Microsoft Research released Fara-7B, a 7-billion-parameter agentic small language model for computer use, capable of executing tasks locally from screenshots. Fara-7B functions as an open-weight Computer Use Agent, predicting mouse and keyboard actions directly from screenshots. Its compact size allows execution on a single user device, which reduces latency and retains browsing data locally. Unlike conventional text-generating chat-oriented Large Language Models (LLMs), Computer Use Agents like Fara-7B control browser or desktop…...
React vs ReactDOM: What’s the Difference? A Deep Dive Into How They Actually Work Together
23+ min ago (540+ words) If you have built even a single React project, you have seen this line more times than you can count: Most developers copy this snippet from a tutorial, paste it into their project, and" move on. But sooner or later, a question comes up: If you have ever wondered about this, you are not alone. This article breaks down the real story behind React and ReactDOM; how they interact, why they were separated from the beginning, and how this architecture powers everything from web apps to mobile apps to VR. React is often described as a view library'but that description does not do it justice. React is the architect of your UI. It understands: React is extremely smart. It reasons about your UI with near-perfect efficiency. But here is the twist: React does not know how to talk to the…...
24+ min ago (586+ words) This is another installment in my Experience Series, where I share detailed reviews of the tools and software I use daily. Previously, I've covered topics like the Zed code editor and Brave browser in video format, but I thought it was time to bring this experience to written form as well. Today, I want to discuss a tool that many of my viewers have asked about but few truly understand'Mini Micro. Despite being relatively unknown in mainstream game development circles, it's a tool that has significantly shaped my approach to game development. Before we begin, I want to clarify that this represents my personal experience. Your mileage may vary depending on your background, preferences, and use cases. My approach to tools has always leaned toward simplicity and minimalism. When I began my game development journey, I was looking for an…...
32+ min ago (54+ words) Check out this Pen I made! Check out this Pen I made! Templates let you quickly answer FAQs or store snippets for re-use. Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink. Hide child comments as well...
Don’t reinvent the AI wheel: How we use existing models will spell success
34+ min ago (573+ words) Earlier this year, Amazon announced that it was eliminating 14,000 management positions because artificial intelligence (AI) tools had rendered those middle-management roles redundant. Amazon isn't the only one'Microsoft, Google and IBM have all announced AI-related layoffs. According to a 2023 report by Niti Aayog, 1.5 million Indian jobs in the IT and business process outsourcing (BPO) sectors alone are expected to be at high risk by 2031. McKinsey believes that as many as 69% of tasks in India's IT services industry can already be automated with existing AI technology, suggesting that as many as 3-4 million jobs in the IT and BPO sectors could be at risk in the near to medium term. The trouble with competing in the race to build better AI models is that it requires us to compete upstream in the AI value chain in a market already crowded by players with…...
VEO 2025: Voice Optimization Transforms SEO
34+ min ago (1616+ words) Have you noticed a subtle yet profound shift in how we interact with technology? Gone are the days of clunky keyword typing; instead, we're engaging in natural, conversational exchanges with our digital assistants. We no longer punch in "Paris weather"; we simply ask, "What's the weather like in Paris this afternoon?" This isn't merely a minor convenience; it's a quiet revolution reshaping the landscape of online visibility. With over 8.4 billion voice assistants active globally and close to one in five individuals (20.5% of worldwide users) embracing this technology, overlooking this trend means losing access to an ever-growing segment of your potential audience. This is where Voice Engine Optimization (VEO) steps in, poised to become the indispensable discipline of 2025. Far from being a mere appendage to traditional SEO, VEO represents a completely reimagined approach to digital communication. Join us as we explore…...
Building SynthDB: A Context-Aware Database Seeder in Rust (and Why I Need Your Help!)
35+ min ago (559+ words) If you've ever set up a test database, you know the pain: This "data" is useless for realistic testing. You can't demo your app to stakeholders, test search algorithms, validate UI formatting, or catch edge cases. I'm building SynthDB to solve this - a zero-config database seeder that reads your PostgreSQL schema and generates statistically realistic, semantically coherent data. The project is in active development and I'm looking for contributors! The key insight: column names contain semantic information. merchant_name " should be a company name support_email " should be a support email (matching the company) mac_address " should be a valid MAC address birth_date " should be a realistic age By analyzing column names and types together, we can infer context and generate appropriate data. How It Works (Current Implementation) SynthDB works in six stages: Schema Introspection - Read tables, columns, constraints Dependency Analysis - Topological sort for foreign key order…...