AI Hustle: News on Open AI, ChatGPT, Midjourney, NVIDIA, Anthropic, Open Source LLMs: Imbue Secures $200M for Cutting-Edge AI Reasoning Models

Welcome to the OpenAI podcast, the podcast that opens up the world of AI in a quick and

concise manner.

Tune in daily to hear the latest news and breakthroughs in the rapidly evolving world

of artificial intelligence.

If you've been following the podcast for a while, you'll know that over the last six

months I've been working on a stealth AI startup.

Of the hundreds of projects I've covered, this is the one that I believe has the greatest

potential.

So today I'm excited to announce AIBOX.

AIBOX is a no-code AI app building platform paired with the App Store for AI that lets

you monetize your AI tools.

The platform lets you build apps by linking together AI models like chatGPT, mid-journey

and 11Labs, eventually will integrate with software like Gmail, Trello and Salesforce

so you can use AI to automate every function in your organization.

To get notified when we launch and be one of the first to build on the platform, you

can join the wait list at AIBOX.AI, the link is in the show notes.

We are currently raising a seed round of funding.

If you're an investor that is focused on disruptive tech, I'd love to tell you more

about the platform.

You can reach out to me at jaden at AIBOX.AI, I'll leave that email in the show notes.

So the big headline here is that MBU, which is an AI research lab that was formerly known

as Generally Intelligent, has recently secured 200 million in Series B funding.

So this is pushing the company's valuation beyond the billion dollar mark, the coveted

unicorn status.

It's kind of interesting because right now we're seeing overall in the tech and the software,

the SaaS landscape, a ton of companies that once were considered unicorns or billion dollar

valued companies and above falling below that billion dollar valuation because they raised

money at sky high valuations back in 2021.

In any case, MBU has a bunch of prominent investors in this round that include Astera

Institute, Nvidia, Crew CEO Kyle, Voked, and also Notion co-founder Simon Last.

So with the latest infusion, MBU's total capital raise now stands at $220 million.

This is pretty impressive, right?

This is 10x all the money, but previous I'd raised 20 million.

So 10x everything they'd previously raised.

And this is really positioning it among the better funded AI startups like AI21 Labs,

Cohere, Adept, Anthropic, so a lot of these bigger ones.

In a recently published blog post, MBU said, quote, this latest funding will accelerate

our development of AI systems that can reason and code so they can help us accomplish larger

goals in the world.

The company maintains its aim to kind of develop AI agents that are not only capable

of complex tasks, but are also practical and safe for real world applications.

So actually last October, MBU emerged from stealth mode with a fairly bold agenda, which

was to explore the underpinnings of human intelligence that AI has yet to replicate.

And initially, the idea was to construct an array of tasks grounded in these, you know,

quote, unquote, fundamentals, and then design AI models to tackle these tasks in intricate

3D environments crafted by the team.

However, the company's strategy seems to have evolved a bit.

So instead of focusing solely on AI in 3D worlds, MBU is now working on models that

are internally useful, such as those capable of coding in a fashion similar to, you know,

like pretty much get cub copilot or Amazon code whisper, those kind of things.

This is really interesting.

I mean, you got to give them credit.

They were doing this, you know, it came out of stealth last October, pre chat GPT launch.

So they're a pre chat GPT hype kind of engine.

So what really sets in views models apart according to the company, it's their ability

to reason robustly.

And in their own words, they said, quote, we believe reasoning is the primary blocker

to effective AI agents robust reasoning is necessary for essentially effective action.

And this involves an array of skills such as grappling with uncertainty, adapting approaches

and making informed decisions, all which are essential for navigating the intricacies

and often unpredictable nature of real of the real world.

So I think what's cool here is they're taking a completely different approach than a lot

of AI models, right?

They're not just another LLM that's able to generate, you know, generate the text.

And I think it's just kind of a good move on their part because there are a lot of even

open source or free LLMs that are coming out.

And I think that that area will be a little bit, it's going to be a little bit inflate,

like there's going to be a lot of players in that space in any case.

So I think what they're doing by taking a new approach to this is really smart.

They're essentially looking at things that AI models typically struggle with that humans

are able to do.

So code in view argues serves as more than just a tool for building scale scalable AI

applications.

We should believe that code can actually enhance an AI model's reasoning ability.

So this is a really interesting concept.

And this kind of echoes a couple of similar sentiments.

We have people at Adept and Google DeepMind that also say that.

And companies also invested in creating AI systems that can autonomously control software

processes or execute tasks based on human interaction.

So in technical terms, in view is investing in, quote, very large models with over a hundred

billion parameters.

And these models are fine tuned to perform exceptionally well on the company's internal

benchmarks for reasoning.

Notably the models are being trained on a compute cluster that NVIDIA co-designed housing,

you know, 10,000 GPUs from NVIDIA's H100 series.

And the thing to note here, right, is they're partnering with NVIDIA.

So they're definitely going to be able to get their hands on some of these GPUs that

are incredibly powerful and are going to help their model.

So I think, you know, from their team's perspective, I think they're doing a fantastic job partnering

with the right people, taking the right approach and building something really novel and useful

in this space that a lot of people, I think, will really appreciate when this launches.

So besides working on these models, though, in view is also, you know, directing efforts

towards creating its own suite of AI and machine learning tools.

So this includes some AI prototypes for debugging and also visual interfaces for AI models.

And the aim is not just to, you know, simply bring these developments to market, but to

also use them as a stepping stone for more generalized, future-ready AI systems.

So that's kind of interesting.

It's not kind of the end goal.

It's just a stepping stone.

I think looking ahead and view aims to lay the foundation for a platform where users

can construct their own custom models, they said, quote, ultimately we hope to release

systems that enable anyone to build robust custom AI agents that put the productive power

of AI everyone's fingertips, end quote.

So the company further noted in the blog post kind of emphasized in that and focusing on

that specifically.

But I think with the latest funding round in view aims to really expedite the realization

of these ambitious objectives.

And I think it's going to be a very interesting company to follow considering the amount of

money they've raised, what they're doing, and some of the really incredible partners

that they currently have.

If you are looking for an innovative and creative community of people using ChatGPT, you need

to join our ChatGPT creators community.

I'll drop a link in the description to this podcast.

We'd love to see you there where we share tips and tricks of what is working in ChatGPT.

It's a lot easier than a podcast as you can see screenshots, you can share and comment

on things that are currently working.

So if this sounds interesting to you, check out the link in the comment.

We'd love to have you in the community.

Thanks for joining me on the OpenAI podcast.

It would mean the world to me if you would rate this podcast wherever you listen to your

podcasts and I'll see you tomorrow.

Machine-generated transcript that may contain inaccuracies.