TECH AND SCIENCE CONTENT BELOG.

 

 The Voice Stack is improving rapidly. Systems that interact with users via speaking and listening will drive many new applications. Over the past year, I’ve been working closely with DeepLearning.AI, AI Fund, and several collaborators on voice-based applications, and I will share best practices I’ve learned in this and future posts. Foundation models that are trained to directly input, and often also directly generate, audio have contributed to this growth, but they are only part of the story. OpenAI’s RealTime API makes it easy for developers to write prompts to develop systems that deliver voice-in, voice-out experiences. This is great for building quick-and-dirty prototypes, and it also works well for low-stakes conversations where making an occasional mistake is okay. I encourage you to try it! However, compared to text-based generation, it is still hard to control the output of voice-in voice-out models. In contrast to directly generating audio, when we use an LLM to generate...

 A concise overview of Transformer-based embedding models, highlighting 4 key aspects: Maximum Token Capacity: The longest sequence the model can process. Embedding Size: The dimensionality of the generated embeddings. Vocabulary Size: The number of unique tokens the model recognizes. Tokenization Technique: The tokenization technique used to create the vocabulary. In general, more advanced models tend to support longer input sequences while maintaining efficient embedding sizes for optimal performance.

 Start Small, Think Big: The Overlooked Power of Basic Skills" Most people today are obsessed with chasing hard, technical skills. Machine learning, blockchain, data science—they sound impressive, but here’s the truth: if you can’t master the basics, the advanced stuff won’t help you. What are these basics? I call them cyber cafe skills. These are the simple, everyday skills that keep businesses and workplaces running: 1. Writing and editing documents in Microsoft Word or Google Docs. 2. Creating compelling Google Slides or PowerPoint presentations. 3. Navigating Excel or Google Sheets, tools that drive decision-making in organizations. 4. Recording your screen for tutorials or troubleshooting. 5. Taking screenshots and creating simple reports. These skills may seem trivial, but they are the backbone of modern workplaces. Imagine being a "machine learning expert" who can’t format a simple document or create a quick slide deck. That’s a mismatch. Before diving into the co...

 

 

 🔰 23 Important Commands in the RUN (Executer) List 🔹 The command dxdiag: Used to check all the specifications of your device.   🔹 The command cleanmgr: Opens the Disk Cleanup tool.   🔹 The command temp: Accesses temporary files, which we delete as they contribute to slowing down the computer.   🔹 The command regedit: Opens the Registry Editor.   🔹 The command calc: Opens the Calculator.   🔹 The command msconfig: A tool to access programs that run with Windows at startup and disable them to speed up the system.   🔹 The command scandisk: Used for disk checking.   🔹 The command cmd: Opens the Command Prompt for Windows.   🔹 The command defrag: Used to stop and defragment the hard drive.   🔹 The command taskman: Allows you to see what is open in the taskbar and manage it.   🔹 The command pbrush: Opens the Paint program in Windows.   🔹 The command debug: Used to ch...

 Understanding Forward and Backward Pass in Neural Networks 🔹 Forward Pass: The input data flows through the network, layer by layer, until it produces an output. This step involves applying weights, biases, and activation functions to transform the data. 🔹 Backward Pass: The model evaluates its prediction by comparing it to the actual result. It then calculates how much each weight contributed to the error and adjusts them accordingly to improve future predictions. This process is called backpropagation and is essential for learning. 🚀 Why is this important? The forward pass makes predictions, while the backward pass fine-tunes the model by learning from mistakes. Together, they enable neural networks to improve over time! #DeepLearning #AI #MachineLearning #Backpropagation #NeuralNetworks