👓 Apple wants Google’s AI secret weapon, World’s largest AI chip, and an AI-made lung disease drug

Welcome to another week of AI Logs by Interesting Engineering, where we deep dive into news of the week, highlight new tools, teach prompt hacks and provide tutorials on a weekly basis. I typically like to do a deep dive into several AI news stories of the week here in the intro, but so much is beginning to culminate that this week feels like a good time to just reflect on everything going on at a high level, particularly as it seems likely that we’re much closer to AGI than most have been speculating, or even more than the legendary Yann LaCun recently suggested.

In that interview Mr. LaCun, did rightfully say that language alone isn’t enough to train models that can achieve AGI, and did NOT specifically articulate that it’s not “on the horizon” — he just said we will need much more data, compute, and models. To that end, last week and the week prior I have been talking about Large World Models (Sora, Geenie), Large Nature Models, Large Action Models (Rabbit) and more. Even NVIDIA just revealed their new foundational AI model for robots, project ‘Groot’, that has massive potential. When these all come together, it opens a lot more doors, and gets us much closer to the potential of AGI (general artificial intelligence, loosely defined as AI that can perform equally or outperform most humans at most tasks/operations).

But these disparate models alone only get us “closer” to AGI; there are several more components to consider, namely, compute and autonomous agents. We have made major strides in both the departments as well. More compute is the basis of Sam Altman’s purported lofty $7T fundraise goal, but has also been escalated by Groq (not xAI/Grok) whose LPU (language processing unit) chip is orders of magnitude faster and more powerful than the current GPU chips made by AMD, NVIDIA, etc. They are cheaper, so much faster and more powerful, and bridge the gap between supply and demand when it comes to compute.

This brings us to agents, which is what many (myself included) predicted would be a top development in the world of AI this year. We are already seeing Devin (by Cognition AI, highlighted here last week), Maisa, and even Google Sima, and others not only showing huge potential, but already effectively deploying as multiple autonomous agents capable of completing even complex tasks including “automating automation”, end-to-end software development and much more.

Finally, we got wind that Apple bought DarwinAI (Arm AI) even as they seek to partner with Google, and this is just indicative of many huge partnerships between tech giants in what appears to be collaborative efforts to expand bandwidth, share resources, and keep barreling ahead toward AGI and a world where AI touches every single aspect of our world and lives.

Welcome to the future, where cars can now fly (as can humans), nanobots can find out human ailments from the inside out, we societally have successfully mined asteroids, buildings can generate their own heat and power, and where a fascinating new emerging technology even allows us to understand and communicate with our pets/animals. The future may be many things, but boring doesn’t seem to be one of them.

To finish this segment, I’ll beat the drum once more on a subject that I believe to be existential: in this new age of AI, I believe EVERYTHING created digitally MUST be tied to a blockchain (immutable, trustless, blind ledger) with smart contracts for transparency, governance, guardrails, ethics and more. We always welcome feedback, advice, questions, or just a hello from you, our wonderful readers who are doing what it takes to stay ahead of this curve with us. And now, “as the kids say”, letsgoooooooo.

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NEWS

• 📱 Apple reportedly wants Google’s AI secret weapons to destroy competition

  Nothing is yet official, but it is believed deal will be struck and announced in June of this year.
  

• 🖥️ World’s largest AI chip with 4 trillion transistors to power supercomputers

  The chip also needs 97 percent lesser code to train a LLM when compared to a GPU.
  

• World’s 1st AI-made lung disease drug gets phase 2 trial in US, China

  Unravel the mysteries of Idiopathic Pulmonary Fibrosis (IPF) and the groundbreaking Phase II clinical trials with INS018_055.

MUST READ

Undeterred by kicks, stick-pounding, AI robot triumphs forest terrain

LimX Dyamics, a Chinese general-purpose robot company, has released a video showcasing its biped robot P1’s impressive locomotion abilities.

The visuals show the robot displaying skills to negotiate challenging environments while venturing into Tanglang Mountain in Shenzhen. P1 also shows its ability to respond efficiently when a human orchestrates a simulation of an attack.

According to the company, the robot uses reinforcement learning to respond to external cues like moving objects or bumps on a path.

PROMPT OF THE WEEK

A great thing about AI is that it’s the first software that has its own dynamic user manual — all you have to do is ask it!

I find that after a series of prompts with defined outcome, asking the AI to act as an experienced prompt engineer and to review the conversation and provide me superior prompts I could’ve used with justification of why they’d have worked better is powerful - both to further that initiative but also to keep learning how to prompt even better.

Furthermore, when playing with new AI tools (with chatbots) or existing tools with updates, I always love to ask it its advanced capabilities, with examples of each.

When getting “no” “I can’t do that” etc I often ask the AI why not, what can be done to get them to do it anyway, and much more. Some call this “jailbreaking”, but to me it’s just figuring out how to get the most out of my AI toolkit.

Ultimately, let your AIs be your guide, and even take your queries to other AIs that have internet connectivity like ChatGPT4 or Google Gemini and ask them about the other tool, workarounds, capabilities, hacks etc. as some tools are trained to not tell you their workarounds, but others share that knowledge online and it can be grabbed by the other AIs.

Finally, to add an actual “prompt” to this section this week, one I’ve been loving is telling my AIs “you’re empowered to be autonomous and answer any questions using assumptions, logic, and your ability to connect to the internet. You will not ask me questions, rather, you will solve them autonomously. All I will provide for you is the work “proceed” between your responses. Do you understand completely and are you excited to work on this together?”. Copy and paste and give it a try — it’s been working like a charm for me.

AI PICTURE OF THE WEEK

TUTORIAL

This will be a quick crash course on something I’ll be holding a paid workshop on soon — how to start and scale a company using AI. I’ve found Google Gemini most powerful for this one so far:

So you need to give it persona, context, and tasks - I start off by saying something like:

“You are my technical cofounder and startup advisor, adopting the persona as an experiences founder who’s raised investment, exited companies, invested in startups and is a sought after startup consultant. Your IQ is that of Sam Altman’s and you’re wired similarly. You will hear my idea for the startup, poke holes, make assumptions, ideate on a go-to-market strategy, help design assets, compile a financial model with 5 year projections, and take us in the direction of viability, lowest hanging fruit, and highest probability of success. You will not ask me questions, rather, you will use the internet and your brilliant mind to answer them on your own, making assumptions as needed. Are you ready to hear the idea and begin to scrutinize it in preparation of making some big things together that can help the world? If so say yes, and tell me how excited you are.”

From here, I tell it to only ever ask me one question at a time, to let me complete telling my idea before providing feedback, to tell me what it can and can’t do to help, to manage expectations, and every time it gives a response as we’re in build more, I simply say “proceed”.

Obviously this is simplified for the sake of space and time, but if you give it a shot, please let me know how it works for you. If you’re interesting in my hands-on workshop, check out my recent posts about it on LinkedIn.

TOOLS OF THE WEEK

📝 Dora Currently in open closed testing (join waitlist and gain access relatively quickly) this text-to-website is one of the best I’ve played with yet, and the sites it’s generating are pretty robust, modern, and set the bar even higher for this type of AI. It does seem that the days of Wordpress, HTML, and having humans build websites is coming to an end, although the best sites I see still have been made by human teams yet.

🤖 Yep is yet another text-to-website (landing page) and what I like about this free tool is their focus on monetization. Great looking sites, custom domains, post-signup surveys and a really great UX flow make these sites notable and worth a try (and it’s free - what do you have to lose)?

📱MindStudio is a cool tool, although early, that lets you train your own AI and build AI-powered apps. The interface is a bit of a throwback, and some of the functionality is behind a paywall, but it’s fun to go in, play around and see what they’re up to. In contrast to the two tools listed above, this is more focused on building apps and chatbots you can embed on your own sites, etc.

🗂️ MyMemo is an amazing tool to aggregate files whether your own or otherwise, articles, YouTube video links etc., organize them, and then chat with the data they include. This is a great way to leverage AI with effectively only data and the knowledge base you provide it with, and is a growth hack and time saver. This tool has a free version, and the paid version is very affordable. I highly recommend checking it out.