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Is DeepSeek the VHS of 2025?

by Ian King
February 8, 2025
in Markets
Reading Time: 5 mins read
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One of many latest shares in our Excessive Fortunes mannequin portfolio is seeing a powerful surge.

On Tuesday, the corporate introduced a significant contract — price over $100 million — from a key participant within the worldwide protection sector.

And as of this morning’s opening bell, its inventory is up 56% since we added it to our portfolio.

In a roundabout means, this firm’s success ties to a current message we acquired from a Each day Disruptor reader.

Let me clarify.

After the DeepSeek-related inventory meltdown final week, Donald H. wrote in with an attention-grabbing thought:

I’m recalling the demise of the Betamax VCR within the face of the cheaper although decrease high quality VHS system that was extra beneficiant in its licensing of the expertise. Will we see that type of a ‘Good System vs. a Good Sufficient System that prices much less’ sluggish fade of super-GPU improvement?

It’s an important query, but it surely isn’t an apples-to-apples comparability.

For one, plainly the preliminary claims about Chinese language startup DeepSeek’s cost-efficient AI had been… exaggerated.

DeepSeek claimed its R1 mannequin solely price $6 million and a couple of,048 GPUs to coach.

However trade analysts discovered that the corporate invested $1.6 billion on {hardware}, together with 50,000 Nvidia Hopper GPUs.

These are high of the road GPUs used for constructing high-performance AI programs.

What’s extra, the analysts discovered that DeepSeek spent nearer to an estimated $944 million on working prices.

That closing coaching run may need solely price $6 million, however your entire enterprise was way more costly.

And while you dig deeper into the discharge of DeepSeek-R1, you’ll discover that there are extra elements at play right here…

The DeepSeek Distinction

As I discussed final week, DeepSeek was in a position to “hack” the traditional means of scaling AI fashions by having a greater mannequin generate the info for them.

OpenAI’s o1 reasoning mannequin is ready to suppose by means of the steps of an issue, and it makes use of that chain of thought to provide you with solutions.

It seems that by primarily distilling OpenAI o1, DeepSeek was in a position to practice its AI mannequin a lot quicker and extra effectively.

And it does appear that the R1 mannequin is extra environment friendly to run than current AI fashions within the U.S., together with o1.

However the greatest issue that makes the discharge of DeepSeek-R1 such a game-changer is that its mannequin is open-source.

OpenAI and Anthropic hold the algorithm and coaching information that drive their ChatGPT and Claude AI fashions a secret.

Google and Meta name their AI fashions open-source, however their coaching information units haven’t been made public, and licenses limit the fashions.

However DeepSeek made its R1 mannequin out there for anybody to obtain, copy and construct on.

As I discussed in final Friday’s Each day Disruptor, the Jevons paradox tells us that with cheaper and extra environment friendly AI turning into out there, we should always see a rise in its use.

This can virtually actually assist speed up innovation within the AI house.

By lowering the necessity for builders to work on specialised fashions, they’ll concentrate on creating specialised functions.

This could get extra individuals to begin utilizing AI, and it’ll assist us begin fixing real-world issues with AI.

However what does all this disclose to us about Donald’s potential: “sluggish fade of super-GPU improvement?”

Right here’s My Take

As you understand, my thesis is that the Trump administration will spearhead a “Manhattan Challenge” to win the race to synthetic superintelligence (ASI.)

I imagine DeepSeek-R1 has modified the trajectory of this mission…

However not in the way in which you would possibly suppose.

Marc Andreesen referred to as DeepSeek’s R1 launch: “AI’s Sputnik second.”

And I agree with him.

However bear in mind how that second performed out.

Certain, the previous U.S.S.R. launched the primary manned satellite tv for pc…

However that occasion acted as a catalyst for the U.S. to land on the moon first and finally win the house race.

I imagine the identical factor is about to occur with AI and Trump’s “Manhattan Challenge.”

China may need launched an incredible mannequin, however America will win the race to ASI.

Right here’s what reader Glenn R. wrote in to say in regards to the state of AI right now:

I’m a retired electrical engineer and an early adopter of Chat GPT (free model). This period is harking back to the early days of non-public computer systems.

These [early computers] relied on crude (learn cheap) magnetic tape (Phillips cassette) and floppy disk storage (an IBM improvement), and a few variations of Tiny Primary and MS-DOS.

The motive force was the widespread want for customized productiveness. That want nonetheless exists.

He’s saying that we’re nonetheless in AI’s infancy. And he’s proper.

The expertise is simply progressing at a charge that we’ve by no means seen earlier than.

U.S. corporations can study from what DeepSeek did to create cheaper and extra environment friendly AI fashions.

As a substitute of a BetaMax vs. VHS state of affairs, corporations may merely provide completely different tiers of AI relying on buyer wants.

However now we have to have superior {hardware} to win the race to ASI.

Give it some thought this manner. At the moment’s PCs are extra highly effective than those we constructed 10 years in the past, however that doesn’t imply we’ve stopped bettering the CPUs that run them.

If something, AI and “super-GPU” expertise improvement ought to go hand in hand.

We additionally must massively develop our AI infrastructure if we need to obtain ASI first.

Once more, the Jevons paradox tells us we are able to anticipate extra individuals to make use of AI even because it turns into cheaper and extra environment friendly.

And this can proceed to drive up vitality and information storage wants.

Look, for all of the hand-wringing about DeepSeek lowering the necessity for hyperscaling our AI infrastructure…

Google appears unphased. The corporate simply dedicated $75 billion to develop AI this 12 months.

Turn Your Images On

To me, that’s the most important information of the week.

It confirms that hyperscalers aren’t chopping again.

And I imagine it’s a optimistic signal for Trump’s “Manhattan Challenge” shifting ahead.

As this example develops, corporations just like the one in our Excessive Fortunes mannequin portfolio that’s already up 56% may more and more profit from greater authorities contracts…

Giving buyers the possibility to make a possible fortune.

Regards,

Ian King's Signature
Ian King
Chief Strategist, Banyan Hill Publishing





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