### AI Chip Development: Strategies for Market Differentiation

Jim aims to revolutionize AI chip development with affordable, open-source solutions for smaller players.

### Building Affordable AI Solutions: A Vision for the Future
* 💡 The company aims to create a **low-cost operation for accelerated chips**, focusing on building a **strong team and shipping products** while engaging **developers and early customers**.
* 🛠 Their unique selling point includes licensing their IP and offering affordable development systems, with an emphasis on **transparency through an open-sourced AI compiler stack** that attracts software engineers.
* 💰 By utilizing less expensive components, they plan to **keep costs down**, particularly by avoiding **high-bandwidth memory chips** that are **costly and limiting**.
* 📊 The market potential is vast, with the company aiming for **$200 million in revenue next year**, having already booked **$150 million**, while targeting smaller players who seek **differentiation**.
* 🌐 Jim believes AI will **dominate computing** in the next decade, emphasizing that the industry is just beginning, with significant transformations in both **hardware and software** on the horizon.
* 🚀 He stresses the importance of **building great products** over execution, citing that successful companies focus on **creating the best possible technology**.
* ⚖ The company is navigating U.S. and China trade restrictions carefully, with a commitment to **compliance** while exploring the **vast business opportunities** available in the evolving landscape.

The money that you're raising, what is
it that you're hoping to do? You're wanting to make a small, cheaper
operation, an option out there for accelerated chips?
Yeah, that's right. We're building out the team.
We're building out our products.

We're starting to ship our products.
And our real mission right now is to bring on developers and early customers.
Let's talk about the customers and what you offer that isn't in the market at
the moment. Jim, what's your selling point?
Well, we have a couple of things.

We licensed our IP and we're building a
business on that for both risk Fi's CPU and I, we're selling low cost
development systems. Like, I'm really interested in hitting a
much lower cost point. Mm hmm.
And then we open sourced our whole AI

compiler stack.
And people like the transparency. They can see exactly what the technology
is doing. They actually it's turned into a great
recruiting vehicle for software engineers.
Interesting. So let's just go first to the price
point.

Just a cheaper offering.
A lot of that is done by having less pricey components.
For example, Nvidia's chips are incredibly expensive.
We know people pay it because of what they offer the full stack in many ways,
but they struggle from a choke

perspective on high bandwidth memory
chips in particular. You don't need them.
Why do you need them? Why do you want them?
Well, it's partly about choices. So there's two choices.
One is if you pick a really expensive

memory technology, you'll never get the
price down, right? And so you need to then make technology
decisions to lower your costs. So we have a in a tensor processor
architecture. We keep the data on chip more.
We have a software stack that's very

good at partitioning A.I.
workloads across multiple chips, and then they can send information and
compute packets to each other without having to go through memory.
And that lowers the memory bandwidth required and also lets it scale more
naturally across many chips.

So I'm a new investor.
You brought me on board. I'm interested, Basil, Samsung.
But you're saying, look, I'm going to do this with more open architecture, with
cheaper offerings. How much of the market should you have
to get?

What sort of price point are we looking
at for your chip offering? Yeah.
So this is really wild. The market is so big.
Like the percent we have to get is actually pretty small to be a real value
proposition. You know, next year we'll die and go to
heaven if we make $200 million.

We have already booked 150 million in
revenue. I'm really interested in finding small
players, early players. People want to own their technology.
People are excited about our software and hardware architecture.
And you know, I want to grow organically

from there.
I think some people will focus on the big guys first.
That's not how new technology introductions go.
You focus on smaller players, people who need a differentiation, and that's what
we're really that's our mission.

So what therefore is the mission
building in in terms of long term value of generative AI, of AI applications of
do you think that we are in some sort of hype cycle?
Do you think that actually this market is as big as many are factoring in?
Well, first of all, we are definitely in

the hype cycle.
There is going to be multiple. And people say, well, Jim, you saying
it's going to go down next year and that's going to go up and down, low pass
filter, all that stuff. Right.
What's really going to happen is AI

is going to dominate computing over the
next ten years and we're just starting and the hardware is going to change a
lot. The software is going to change a lot.
Like one day you read in the papers, alums can do anything, and the next day
you read they've hit a limit. 

Ignore all that stuff.
We're just starting this. There's going to be massive
transformations. So what I really want to start to have
is great computer designers, general purpose CPUs, AI
processors, chip design systems, design, 

software design, and then the open
source stuff is really interesting because that engages a community.
People are really passionate about that to contribute back.
This is why you're thinking about your own talent team.
You've managed talent, as we said, sort

of across the board.
You began like you were integral to the chip design process in the US.
When you think back to DC and then the work that you did at AMD.
Moving to Apple, you were Intel and I just have to go there on this day that
Pat Gelsinger hands in his room, hands

his hat on off, he's going to be
resigning. Many would say it's because they didn't
get into AI quickly enough. That was prior to him.
What do you make of the transition? Well, it's hard to say.
So I like Pat personally.

I've met him a number of times.
He's a smart guy. He really cares.
I think the market focuses too much on stuff like execution and transition.
The way you make money, get customers is build great products.
Like Steve Jobs was the best at this.

Focus on the product, make the best
product you possibly can. And I think they need somebody way more
hands-on, really focus on product and they need to stop talking about
execution. All the nonsense, right?
When they make the best product, the

best fab, the best chip, the best CPU
accelerator, they'll do fine. Jim.
When you're thinking about all of the areas you want to own, how much does
U.S. and China factor into your growth story?
So, first of all.

We are building open source software
RISC-V based technology. We think that's an open platform.
There's a lot of people interested in that.
At the same time, you know, there are, you know, restrictions by the US
government and trade rules.

We have really good lawyers and trade
compliance people. We're very closely with those guys.
We want to do the right thing both for the business and for, you know, being
compliant to what's going on. And it's a changing world and we're very
involved in that short run.

Our business possibilities are really big. And, you know, if China plays in that, that'll be interesting. If it doesn't for various reasons, that's fine.

Tenstorrent's Keller: We're in an AI Hype Cycle

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Bloomberg Technology

Focus on building a team, products, and shipping to early customers and developers.

Selling point: low-cost development systems and open-sourced AI compiler stack.

Licensed IP used for both CPU and AI, aiming for a much lower cost point.

Open-sourced AI compiler stack improves transparency and helps recruit engineers.

Cost Reduction Strategies and Technological Choices

Lower costs achieved through less expensive components, avoiding high bandwidth memory chips.

Choosing less expensive memory technology to lower overall costs.

Utilizing a tensor processor architecture to keep data on-chip and optimize software for workload partitioning across multiple chips.

This reduces memory bandwidth requirements and enables better scalability across multiple chips.

Targeting a small market share to achieve a significant value proposition.

Projecting $200 million in revenue next year, having already booked $150 million.

Focusing on small, early players who want to own their technology and are excited about the software and hardware architecture.

Organic growth strategy targeting smaller players needing differentiation.

Acknowledging the current hype cycle but emphasizing AI's long-term dominance in computing.

Expecting significant transformations in hardware and software over the next ten years.

Ignoring short-term fluctuations and focusing on long-term growth and innovation.

Emphasis on building a strong team of computer designers and leveraging open-source contributions.

Discussion of the speaker's experience in chip design and leadership roles at various companies.

Commentary on Pat Gelsinger's resignation from Intel, suggesting a need for stronger product focus.

Emphasis on the importance of creating great products over focusing on execution and transitions.

Advocating for a hands-on approach to product development and minimizing distractions.

Belief that creating superior products will lead to success.

Geopolitical Considerations and Compliance

Building open-source, RISC-V based technology for a global market.

Acknowledging US government restrictions and trade rules.

Maintaining strict compliance with trade regulations and working closely with legal experts.

Adapting to a changing global landscape and remaining open to opportunities in various markets, including China.