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Okay
So get this um
We're going to get a sneak peeak into the mind of alexander wing the ceo of scale ai
Oh
Well you've probably heard of scale ai
They're like the data infrastructure company in ai right now
But here's the thing
This isn't one of those interviews
Where he's altimated big
And it's all polishing perfect
Right right
This is different
Yeah
We're listening to an interview
He did Oh
I think it's the self part commons youtube channel
Oh Cool
And 对
He was way back like before scalally i really took off
So it's
It's to like we're 're travelelling back to the um
What do they calall the minus one stage of the company
I like that
Yeah
The minus one stage
When he was just figure ing things out
Yeah
And he talks about you know this like existential angked that you feel feel you're starting out
Which i think is super relatiable
It makes you realize that even someone like wying felt that same uncertainty
We all have
When we're like mand i'm
I really going to do this
Yeah
Launching something new like what are the chances of actually making it
Yeah Yeah
Actually tually ses ses this challogy of the ungger games sasays really really start up world
It feels like that you most just don't survive that those early years
It's sure
But waang's approach to coming up the ideas is really interesting
He talks about how he was really inspired by that poalgram essay
You know had to come up with start of ideas
Oh Yeah
That's a classic legendary in the startup
For
For totoally
It's all about about like envisioning the future and looking for those opportunities
That other people are missing exactly so waying was probably thinking okay
What's going to be huge in the future
What problems are being solved yet exactly
But you know it's not enough to just have a good idea
He really emphasizes the importance of conviction
So once he landed on the idea for scale ai
He just knew it was going be big
Even if nobody else w
Yeah
Ah and i bet a lot of people listening
Have felt that way about an idea at some point
Oh
Absolutely that good feeling
You know it can be so powerful
Learn that story about how you went bought the domain naames scaled out ai like before you had all the details figured out h
Yeah
That's a great example
You just knew
Yeah
That's a great example of how important is to act on those convictions
Yeah
Like that belief in your idea
It can actually be a magnet
Yeah
It draws in the talent
The resources you need to make it real
I love that
It's like that belief itself starts to shape reality
Speaking of shaping reality
You know waying has some pretty insightful observations about competition
Like how competition really works in the enterprise world
Especially
When you're dealing with these big organizations like government
Yeah
He uses this phrase perception is reality
Which really stuck with me
It's so sure like in a complex world
Especially with something like ai people just looking for someone to like cut through all the noise
Yeah
And present a clear vision
Totally
He actually tells always story about palent here
Oh Yeah
Know know data analyyticcompany they're known for their really aggressive sales
Tactics
And when ying actually observe this first hent
It's almost like they've master the art of perception
You know
Even if it doesn't always lline up perfectly would like the reality of their products
Yeah
I mean think about it
If you're a decision maker at a huge company or a government agency
You're bombarded with information all the time
Yeah
So the companies that win are often the ones they can just cut through all that cluttter and tell a compelling story
Even if their techch is inobjectively better it's true
So it's not just about building a great product
It's about telling ling great story
It's but of course you can't just cost on a good story
Forever right you have to deliver right you have to get result
And this is where i think wang's background in um competitive programming
我的的really shines through
Oh
You know he approaches problems with this very systematic mindset
And he really argues that startups need to apply that same rigor to the like unsexy operational challenges
You know the kind of stuff that doesn't make headlines
But can actually make or break a business
But the stuff nobody wants to deal with
But it's so important
It reminds me of how um like some tech companies
Like facebook
They used to promote their most productive engineers
Even if they weren't working on the like flash y projects
That's interesting
Sometimes the biggest impact comes from solving those seemingly mundane problems
I can really like slow a company down absolutely
And it sounds like that's big ked into scale as culture
They value economic impact over the perceived coolness of the tech
I love that it's all about what's actually going to move the needle
Not just what sounds impressive on a pitch deck
And that's such a valuable lesson for anyone really whether you're starting a company or just trying to be more act at at king
Now now easeasy get caught up in the hype
But sometimes the bigwins come from those kind of unsecxy behind the scenes
Efforts 没sure
It's about finding ways to apply that same problem solving intensity to any challenge are facing absolutely and speaking of challenges waye also has some some pretty interesting thoughts on the bigger picture
Yeah
Particularly like the global forces that are impacting ai
Oh Yeah
Totally yeah
This is where it gets really interesting
You know we start to see how ai isn't just something like isolated tech bubble
It's intertwined with geopolitics in a big way absolutely
Yeah Yeah
It's ah you almost can't talk about ai today without talking about geopolitics and wangare are shying away from that at all you know he actually
Even even ls for more ah ah ah political ereracy inself in valley
But
But he's not
You know he's not talking about like picking sites are getting into you partisan politics or anything
It's more about just understanding how these bigger global forces are going to shape the future ai
Like how the the rising tensions between the us and china
Yeah are going
Going impact act right
Even if
Even if the tech companies themselves try to stay out
Out of
Exactly yeah
Uah
He points out something pretty startling
Actually
He says that the first you know the first successful replication of open ice chat upt came from a lab in china
Wow
Which is just es to show
There's
There's very little research gap between the us in china
In terms of like core ai capabilities
So it's just a scientific race
Anymore
It's like which countriy's tech ends up being adopted globally
Which becomcomes the standard
It
It's almost like entering a new kind of tech cold war
Yeah
Where control of the what he calls the ai stack is the prize and
And undersay what he means by ai stack
It's like imagine all the layers of software and hardware
That make ai possible from the chips
Yeah
To the algorithms to the cloud platforms
I mean taiwan is like a major hub for chip manufacturing exact tly any disruption
There would send shock wave through the whole ai ecosystem totally
It's
It's a reminder
That these geopolitical issues aren't just like it's abstract headlines there are directly connected to the future of ai
They are and honestly like
Like a lot of tetechnology that we rely on every day
You know it makes you realize that understanding politics is almost as important as understanding the tech
Itself self ablutely tely and aawareness is something that wing seems to encourage in ounoundtoo
You know know talks about how like it different points in the company's journey
What you're building by be the hot new thing
Yeah
Where might be totally uncool too it's true
Yeah
Who's paying attention to it at that moment
It's like writing a wave
You know you've gota be prepared for those upsent downs
And not get swept away by the hype
Whether it's good or bad
Hype right exactly remember he was talking about about in videa
Which is not like a huge player and ai now
Oh Yeah
But they went through those cycles
Where they were like the unsexy company
And then obvisted everybody wanted a piece of them
Yeah
They were the pixand shovels during the gold rush
Oh
The gold rurush siof you know died down yeah
And they were just left standing
Exactly this incredibly valuable infrastructure
And now the gold rush is back back
And they're like perfectly position
Exactly tly and know know was being of being uncool wang is surprisingly critical of some aspects of um like silking valley culture yeah
Intereted it's almost like he's seeing the dark side uh of that move fast and break things
Mentality
He does he actually says
And this is a direct quote
Okay
That helicgan values filled with people who don't really believe anything
And get all their ideas off of twitter and parties
Yeah
That's got a thing thing for some
But there's some truth to it alright
Yeah so easy to get caught up in the echo chamber
Especially you're surrounded by people who are all chasing the same trends
It's ah but waks challengge aging us to think independently to develop own convictions
And not be afraid to go against the grain
Yeah
Ah what do you think about that i mean it definitely resonate with me
It so easy y get swept up up
And everyone elelis doing
Especially ally to feel that's moving is fast as ai right
But the people who really make an impact
We're often
The ones who forged their own pass
Yeah And
And forging your own path doesn't mean being stuborn or refusing to learn
You know weighing talks about the importance of having like a mechanism by which you're constantly learning from the ecosystem
I like that
Yeah
Like staying open
Yeah being open to new information
Even if it challenges your existing beliefs
And that's where finding those truly independent thinkers
The people who aren't afraid to go against the crowd can be so valuable
Yeah
Where do you find those people right
That's the question well
Why i'm actually sugggest outouta silicicon valley for those insights so dimentionons um substack as an example of a platform
Where you can find like really insightful rating from people who are thinking differently
That's cool
Yeah Yeah
It's about surrounding yourself with people who challenge your assumptions
Yeah
And help you see the world from new angles exact those perspectives can be so valuable
Oyeah
When you're trying to build them truly new right you know and beyond those big picture ideas and those independent thinkers
There's one source of learning
That wang says
You should never ignore your customers
Oh Yeah
He has this really 不
But powerful philosophy customers are just always right
It's so true
It's about like yeah
Putting your ego aside yeah
And really listening to what your customers are telling you
Even if it's what you want to hear
Yeah
Even if it's painful
Their feedback is the most valuable data you can get
He actually go so fast to say that working with large enterprises can be like dealing with cancers
Oh wow
There's so like complex and bureaucratic
But if you can navigate those complex
Yeah
The rewards can be huge
It's like anything worthwhile
It's going to be challenging right
But if you can figure out how to solve those unsexy operational proms
Yes
The ones
That nobody else wants to deal with that's where you can really differentiate yourself
It ties back to what we were talking about earlier right that focus on solving the unglamorous probleproblems ones that might not be trendy right
But can have a huge impact on your business
Yeah
And some of of those problems lead you to some unexpected opportunities totally inawain points out that while a lot of start tups focus on small and medium businesses to gain initial traction
They're often these like each opportunities within larger enterprises that can be really lucrative interesting
Yeah
It's like finding that hidden popotive value
Yeah
Nobody else is paying attention
Yeah
He 's this really interesting anallogy
He says that in the start up world
He saies often tried to model themselves
After the successful companies at the moment
Yeah
It's a constant cycle right
It's like this cycle of perfect competition
Where everybody's fighting for the same slice to the pie
Trying to be the next big thing
Yeah
You rather the disrupor or the disrupted
Exactly
Yeah
But then there are those companies that focus on like a more fringe idea
Something that might not be popular at first right
But then it ends up taking off
And then everybody starts copying that company
And then everybody starts copying in that company
Exactly
And the cycle repetes itself
Yeah
It's like chasing the tae of innovation
You know
Always trying to catch up to what's already working
Yeah
Instead of carving out your own path
Exactly
So the key to be be head of that curve
Yeah
To identify those emerging trends before they become overcrowded
It takes a certain amount of vision and risk tolerance
It is something that waynarargues sililcome valley for all it's talk about disruption
Can actually be pretty resistant to that's interesting
Yeah
It's almost paradoxical
You know silan valley wants to be seen as this hub of innovation
Yeah
But also this strong tendency to follow what's already working to chase what's already proving him
So how do you break out of that cycle right do you identify those truly disrupt of ideas
That everyone else is missing
When enencourages founoundto no know
Think it dependently no and to not be afraid to challenge the status quoal
It's easy to say harder to do right yeah
He suggests you 're looking for opportunities outside of the traditional techups um places for people are thinking differently and approaching problems from new angles finding those like pocketive innovation
Exactly yeah
It's about be willing to explore the unknown to take risks
Yeah
To trust your own instincts
Even when everyone else is telling you you're wrong
That's powerit's a powerful message um
And it really resonates with that idea of finding those unsexy opportunities
Um that nobody else is painattention
You know
And it ties back to we 're talk about earlier that need for political literacy
The world is changing rapidly
And the forces shaping the future of ai
Aris technological
There popotical al socieeconomic
It's all connected it
It's all connected yeah
And you can't just focus on building a better algorithm
You have to understand the context in which that algorithm is going to be used right
The forces that are going to pe pe its adoption 对ai and the potential unintended consequences that might arise
I think you're not just building a tool
Theyshashaking fufuture actly it's like we've been on this incredible journey with waning
You know from those early start up struggles to late grappling with geopolitics and even dissecting with ilicicon valley culture
And throughout it all he's just kept it real
You know he's honest about the limitations of ai
And he even calls out some of the hype
That's surrounds the field
Yeah
Which apprereciate refresh
Especially
When you consider how much height there is in the tech world
In general
Oh
Totally remember how he was uh pretty blunt about ai agents
Oh
Ah even calling them uh
I think he said a bullship machine at
At their current stage
It sound harsh
But
But it's actually really insighful
I think so too
He's pointing out that just because an ai can generate human sounding text doesn't mean it understands what it's saying right so like you would mistake a parent limicking human speech
Yeah for actual understand it exactly so how do we avoid falling into that trap
How do we develop that critical eye to distinguish between you know ai ffluency in actual intelligence
That's the million dollar questions
Especially
When these models are getting so good at mimicking human conversation
I know it's getting harder and harder it really i don't think there's like aa simple answer
But when does emphasize yeah
The importance of recognizing human bias in these model that's huge
Yeah
I mean the ai is only as good as the data
It's trained on right
And that data is often shaped by you know our own human limitations and biases
It makes you think about all the subtle way that bias can creep in even if we're not consciously aware of it
It's a reminder to be extra vigilant
Especially as we start to rely on ai more and more decimake ty awness yeah
Exactly do you think that kind of awareness is something we can like cultivate
I think
So it starts with acknowledging that bias exists even in the most sophisticated ai models
And it means asking critical questions about the data that's being used
The assumptions that are being made
And the potential unintended consequences that might arise yeah
That's a lot to consider it's a lot
It's almost like we need to develop a new kind of literacy
Like an ai literacy
Who i like ai literacy that goes beyond d understanding the technology yeah
Lls into the ethical and social implications
So it's not just about the how
It's also about the why
Exactly yeah
The why and the who in the forward yeah
It's almost like we have to become ai ethists in our own right and a way yeah
We can't just blind dly trust the systems yeah not understand how they work yeah
And where they might fall short totally
And that leads to another big question
That wanging brings up what does it actually mean to be intelligent
Oh
That's a good one right think about processing information quickly and efficiently
Ah or is there something more to it is there there certain level of creativity or inside that sets humans apart right
I'm the most advanced ai right i mean that's a question
That phillosopers have been wrestling with for central serious exact
And now it's becoming increasingly relevant in the context of ai for sure
And i think when is challenging us don't as users and developers of these technologies to engage with these questions
Not just focus on the like technical advancement
Absolutely he also highlighed the importance of creativity and independent thinking in the ai space
Yeah
It's easy to get cut up in the race to build you know bigger and better model right
But he argues that we also need to think about how to use these models in new an innovative way
Ways
Ways that might not be obvious
At first he mentioned perplexity ai as an example
Yeah
They found success by focusing on a specific nnhe um using large language models to improve search and becoming the best at that one thing said
Said trying to build a like do it all ai solution right that cus that focus is so key
Yeah in a space
That's moving as fast as ai is easy to get distracted by every shiny new thing that comes along true
But when 's own journey with scale ai
But a testament to the power of sticking with a vision
Yeah
Even when it's not the popular obvious choice
Yeah
Know he saw a critical need in the ai space
Data infrastructure
And he it's waa struata leader in that field
He didn't get side tracked by the hype or the competition
He still focused on solving a real problem
And that focus paid off to great great lesson
Yeah
For one building something new new
Whether it's a company a product
Even just a new skill exactly
And it beond d pracactical lessons
I think there's something the inspiring about wine story
I agree it's a reminder
That even in a feel there's complex and competitive as ai individuals can still make a huge impact
I love that it takes a vision
Resilience and a willingness to chart your own course
So as we wrap up this deep dive into you know egganderwings inside
Let's turn over to you the listener
If you were starting an ai company today
What problem would you solve
What unique perspective would you bring to the table
And how would you navigate the hype
The competition
The ever changing landscape of this
The exciting field we've covered a lot of ground today to the ninedy greedy of start up life
To the geopolitical forces shaping ai
And even the philosopofficiical question that this technology raises hopefully this deep dive is given
You know some new perspectives
Some food for thought
Maybe even some inspiration to go out and make your own mark on the world of ai
Absolutely keep learning
Keep questioning and keep pushing the bounders were all on this journey of exploring the possibilities and implications of ai together
And the future is wide open
