Manus, the new AI product that everyone's talking about, is worth the hype.
This is the AI agent we were promised.
Deep Research+Operator+Computer Use+Lovable+memory.
Asked it to "Do a professional analysis of Tesla stock " and it did ~2wks of professional-level work in ~1hr!
There are thousands of hit songs, but far fewer hit software products.
Like songwriting, building a hit product is about creativity, craft, and taste—not credentials.
A Berklee degree doesn’t guarantee Taylor Swift hits. Product builders are artists. Treat them as such.
I built and sold https://t.co/0PDma01Bry for $1.3 billion to Adobe, and along the way, I received plenty of advice that turned out to be entirely off the mark. Here's a look at some of the most glaring misdirections:
1. "As CEO, focus on executive business tasks." This couldn't be further from the truth. The core purpose of any company is the product it offers. As CEO, your primary role is to ensure that this product is the most valuable it can be for your customers. It's not just about overseeing; it's about being integrally involved in delivering quality.
2. "To scale, you need to decentralize decision-making." Actually, the opposite is often more effective. As organizations grow more complex, centralized decision-making can slice through red tape and foster quicker action. Even in environments that champion decentralized processes, top-down leadership often proves to be the fastest route.
3. "CEOs shouldn't get caught up in the details." This is a myth. Consider leaders like Steve Jobs, Elon Musk, Mark Zuckerberg, Brian Chesky, and the Collison brothers — all are/were deeply involved in the intricacies of their businesses. Emulating their approach is not misguided; it's a blueprint for hands-on leadership.
4. "10X engineers are a myth, and believing in them is harmful." Quite the contrary. In many teams, a small fraction of the workforce often generates the majority of outcomes. Recognizing and nurturing high-performing individuals isn't just realistic—it's crucial.
5. “You must validate every decision with customer research.” Contrary to popular belief, not all successful decisions stem from extensive customer research. Many of my pivotal choices were guided by my own instincts and preferences for the product. Trusting your vision and building a product that you would use yourself can lead to creating something that resonates deeply with your customers. Personal intuition can be a potent tool in product development.
With many 🧩 dropping recently, a more complete picture is emerging of LLMs not as a chatbot, but the kernel process of a new Operating System. E.g. today it orchestrates:
- Input & Output across modalities (text, audio, vision)
- Code interpreter, ability to write & run programs
- Browser / internet access
- Embeddings database for files and internal memory storage & retrieval
A lot of computing concepts carry over. Currently we have single-threaded execution running at ~10Hz (tok/s) and enjoy looking at the assembly-level execution traces stream by. Concepts from computer security carry over, with attacks, defenses and emerging vulnerabilities.
I also like the nearest neighbor analogy of "Operating System" because the industry is starting to shape up similar:
Windows, OS X, and Linux <-> GPT, PaLM, Claude, and Llama/Mistral(?:)).
An OS comes with default apps but has an app store.
Most apps can be adapted to multiple platforms.
TLDR looking at LLMs as chatbots is the same as looking at early computers as calculators. We're seeing an emergence of a whole new computing paradigm, and it is very early.
Code Interpreter Beta (rolling out to ChatGPT Plus) is quite powerful. It's your personal data analyst: can read uploaded files, execute code, generate diagrams, statistical analysis, much more. I expect it will take the community some time to fully chart its potential.
To turn on:
In ChatGPT on bottom left click on name > Settings > Beta features > turn on Code Interpreter.
Snowflake's updated S-1 shows that Berkshire Hathaway is going to purchase $573M total of Snowflake shares at the IPO price. Warren Buffett enters enterprise software.
Can't find an example of major innovation where experts who knew too much made change happen! Amazon vs Walmart, Tesla vs GM, Spacex vs. Lockheed, Twitter/Youtube/FB vs media, Genentech vs pharma, AirBnB vs hotels, Uber vs. taxis,... Experts can explain "why not" instead of "why"
Today on US Google & YouTube homepages we share our support for racial equality in solidarity with the Black community and in memory of George Floyd, Breonna Taylor, Ahmaud Arbery & others who don’t have a voice. For those feeling grief, anger, sadness & fear, you are not alone.
Congrats to Geoff Hinton, Yoshua Bengio & Yann LeCun on winning this year's Turing Award. Their groundbreaking work on deep neural networks has transformed not just computing and AI, but nearly every other scientific field today https://t.co/EMJvX9UUip