Technology

The third Sequoia Capital AI Ascent just wrapped up in San Francisco. After watching all the available footage on YouTube, it’s clear there were some game-changing insights—essential reading for any AI founder or industry professional. 1. The Shift in Revenue Logic: Selling Outcomes, Not Tools AI isn’t about selling software—it’s about selling results. Pricing is shifting from features to outcomes. Old model: A CRM sells “customer management tools.” New model: An AI-driven CRM agent sells “X closed deals per month.

In the ever-evolving world of AI-driven design tools, understanding how systems like Google Stitch generate their outputs can provide valuable insights for designers and developers. Recently, I successfully reverse-engineered Stitch’s design prompts using methods inspired by online “trickery” techniques. Below, I’ll share the findings. The Design Prompt Here’s the reverse-engineered prompt used for both tools (refer to the uploaded image for the original text): You’re a friendly UX/Product designer that’s an expert in mobile and web UX design.

The Hard Truth About AI in the Workplace Slapping a chatbot into your company Slack isn’t “AI adoption.” Too many businesses make these mistakes: AI becomes just another tab employees forget to open. Models improve, but answers stay generic — no deep alignment with actual work. Information chaos persists because AI isn’t wired into daily workflows. The root issue? AI is often bolted on, not built in. Feishu’s Fix: AI That Works Where You Work Enter Feishu (Lark) Knowledge Q&A, launched today.

Alibaba just unveiled Qwen 3, its latest open-source large language model (LLM), and its flagship Qwen3-235B-A22B now rivals DeepSeek R1, Grok-3, and Gemini-2.5-Pro in benchmarks. With hybrid inference and enhanced Agent capabilities, Qwen 3 signals a shift — open source is China’s key to global AI dominance. The New Open-Source Power Duo: Qwen + DeepSeek For years, the open-source LLM ecosystem was ruled by Meta’s Llama and Mistral. But today, DeepSeek and Qwen are taking over.

We delve into the transformative ideas presented by OpenAI Agent Researcher Yao Shunyu during his discussions at CS 224N and Columbia University. We Stand at the Midpoint of AI For decades, the crux of AI has revolved around developing innovative training methods and models. This trajectory has proven effective: from defeating international chess and Go champions to outperforming most on SATs and bar exams, winning gold medals at IMO (International Mathematical Olympiad) and IOI (International Olympiad in Informatics) — milestones like DeepBlue, AlphaGo, GPT-4, and the O series were born from underlying training method innovations, including search, deep RL, scaling, and reasoning.

You’ve also jumped on the Dify.ai bandwagon? Smart move! It’s a seriously cool platform for building AI apps. But, like any powerful tool, it can get a little… expensive if you’re not careful. I’ve been playing around with it for a while now, and I’ve picked up a few tricks to keep my token usage (and my credit card bill) down. Think Before You LLM This is the big one. Every time you hit that “Run” button and the Large Language Model (LLM) spins up, you’re burning tokens.

This year’s Product Hunt Golden Kitty Awards are a love letter to AI—and developers are eating good. From code assistants to synthetic video wizards, tools that blend human creativity with machine speed dominated the rankings. Let’s break down the winners (and why your workflow needs them yesterday). Top Dog: Cursor The AI Pair Programmer That Just Gets You Forget clunky IDEs. Cursor, crowned Product of the Year, is where coding meets conversation.

Deploying Ollama DeepSeek and RAGFlow locally allows you to run powerful natural language processing (NLP) models in your own environment, enabling more efficient data processing and knowledge retrieval. Let’s get started. 1. Environment Preparation First, ensure your local machine meets the following requirements: Operating System: Linux or macOS (Windows is also supported via WSL) Python Version: 3.8 or higher GPU Support (optional): CUDA and cuDNN (for accelerating deep learning models) 2.

Most people are using DeepSeek wrong. After burning the midnight oil testing this thing (and drinking enough coffee to power a small nation), I’ve cracked the code. Forget everything you know about ChatGPT – this is a whole different beast. 1. The Biggest Secret: Ditch the Prompt Templates Don’t use rigid “professional prompt formulas.” DeepSeek thrives on context and purpose, not step-by-step instructions. Take it as a clever intern who needs clear goals, not micromanagement.

Working in a startup is a great experience, but it’s not always easy to find the right one. Here are some tips to help you evaluate a startup before joining: Deep Understanding of the Founding Team: You can never know too much about the founding team. Are they responsive? Can they accurately judge people? Are they humble enough to listen to others’ advice? It is recommended to directly participate in their team meetings, observe their working style, and after a few times, you can judge whether the team is reliable.