has become the single most effective approach for me to solve problems. Most problems I encounter at work can be solved effectively by utilizing agents. This is in contrast to manually solving tasks or coding up a solution yourself. In this article, I’ll give a high-level overview of how I approach problems and solve them …
Image by Author Contents# Introduction# 1. OpenRouter# 2. Olostep# 3. Tinker API# 4. SerpApi# 5. MOSTLY AI Generator API# Wrapping Up # Introduction You’ve probably heard people talk about APIs a lot. Basically, an API allows a software to ask another piece of software for help. For example, when we use our weather app, it might use a real-time API to get …
In August, we previewed Genie 3, a general-purpose world model capable of generating diverse, interactive environments. Even in this early form, trusted testers were able to create an impressive range of fascinating worlds and experiences, and uncovered entirely new ways to use it. The next step is to broaden access through a dedicated, interactive prototype …
AI world model now available for Ultra users in U.S. Read More »
in the federated learning series I am doing, and if you just landed here, I would recommend going through the first part where we discussed how federated learning works at a high level. For a quick refresher, here is an interactive app that I created in a marimo notebook where you can perform local training, …
Federated Learning, Part 2: Implementation with the Flower Framework 🌼 Read More »
Image by Author Contents# Introduction# Defining Multimodal Artificial Intelligence: From Single-Sense to Multi-Sense Intelligence# Understanding the Foundation Trio: Vision, Voice, and Text Models# Exploring Emerging Frontiers Beyond the Basics# Implementing Real-World Applications# Navigating the Emerging Multimodal Infrastructure# Summarizing Key Takeaways # Introduction For decades, artificial intelligence (AI) meant text. You typed a question, got a text response. Even as language models grew …
The Multimodal AI Guide: Vision, Voice, Text, and Beyond Read More »
A note from Google and Alphabet CEO Sundar Pichai: Nearly two years ago we kicked off the Gemini era, one of our biggest scientific and product endeavors ever undertaken as a company. Since then, it’s been incredible to see how much people love it. AI Overviews now have 2 billion users every month. The Gemini …
Introducing the latest Gemini AI model from Google Read More »
Segment Anything Model 3 (SAM3) sent a shockwave through the computer vision community. Social media feeds were rightfully flooded with praise for its performance. SAM3 isn’t just an incremental update; it introduces Promptable Concept Segmentation (PCS), a vision language architecture that allows users to segment objects using natural language prompts. From its 3D capabilities (SAM3D) …
SAM 3 vs. Specialist Models — A Performance Benchmark Read More »
Image by Author Contents# Introduction# Identifying Where Python Struggles in Data Science Workloads# Using Python for Orchestration and Rust for Execution# Understanding How Rust and Python Actually Integrate# Speeding Up a Data Operation with Rust# Rust Tools That Matter for Data Scientists# Determining When You Should Not Reach for Rust# Conclusion # Introduction Python is the default language of data science for good …
Introducing D4RT, a unified AI model for 4D scene reconstruction and tracking across space and time. Anytime we look at the world, we perform an extraordinary feat of memory and prediction. We see and understand things as they are at a given moment in time, as they were a moment ago, and how they are …
D4RT: Unified, Fast 4D Scene Reconstruction & Tracking Read More »
generate customer journeys that appear smooth and engaging, but evaluating whether these journeys are structurally sound remains challenging for current methods. This article introduces Continuity, Deepening, and Progression (CDP) — three deterministic, content-structure-based metrics for evaluating multi-step journeys using a predefined taxonomy rather than stylistic judgment. Traditionally, optimizing customer-engagement systems has involved fine-tuning delivery mechanics such as …
