Dario Ameudi challenges $ 6 million in Dibsic: What Antarbur thinks about the latest Amnesty International movement in China.

The world of artificial intelligence shook last week when DibsicAI, Chinese, has announced the latest linguistic model that seems to match the capabilities of the American American American systems on a small part of the cost. The advertisement widespread Selling market This has eliminated nearly $ 200 billion in the market value of NVIDIA and raised hot discussions on the future of developing artificial intelligence.

The Narrative That Quickly Emeged Suggested that Deepseek had fun HAD Spent Billions to AcoCOPLISH. This interpretation sent shock waves across Silicon Valley, where companies love and manAnd Google He justified huge investments in computer infrastructure as necessary to maintain the technological edge.

But amid market turbulence and unimaginable newspaper addresses, Dario AmoudiThe co -founder of Anthropic and one of the pioneering researchers behind the great language models today has published a detailed analysis that provides a more accurate perspective on Deepseek’s achievements. for him Blog post

Below are the four main visions of Amodei analysis that reshape our understanding of Deepseek:

1.

Dibsic mentioned Development costs يجب أن يتم عرضها من خلال عدسة أوسع ، وفقا لأمودي. in AnalysisDirectly defies the popular interpretation:

“Deepseek does not ‘do for $ 6M What Cost Us Ai Companies Billions.” I can only talk about Anthropor, but Claude 3.5 Sonnet is a medium -sized model costing $ 10 million for training (I will not give an accurate number). Also, 3.5 Sonnet was not trained in any way that included a larger or more expensive model (unlike some rumors). “

This shocking revelation mainly changes the narration about the cost efficiency in Dibsic. When considering this Sonata It was trained 9 to 12 months ago and still outperforms the Deepseek model in many tasks, and the achievement appears more with the natural progress of the costs of developing artificial intelligence rather than a revolutionary achievement.

The Timing and Context also MATTER SIGNIFICANTLY. After historical trends to reduce costs in developing artificial intelligence – which is estimated at 4x Amoii annually – it appears that the Deepseek cost structure in a large -end and not largely before the curve.

R1 Deepseek Model

and R1 Is Crucial for Undersanding Deepseek’s True Technology Advancement. V3 represents real engineering innovations, especially in managing the model.“Pay limits”” road.

This insight helps to clarify the reason that the dramatic market reaction is in a misplaced R1. R1 has been added mainly to reinforcement learning capabilities to the V3 Foundation – a step that many companies are currently taking with their models.

3. The total companies’ investment reveals a different image

This revelation greatly restores the narration on the efficiency of Deepseek resources. Although the company has achieved impressive results through individual model training, its general investment in developing artificial intelligence seems to be almost similar to its American counterparts.

The distinction between model training costs and the total investment of companies highlights the continuous importance of great resources in developing artificial intelligence. IT Suggests that While Engineering Efficience Can Bey Improving, Remaining Competitive in Ai Still Requires Significant Capital Investment.

Amodei describes the current moment in developing artificial intelligence as unique but transient:

“We’re therefore at an interesting ‘crossover point’, where it is temporarily the case that several companies can produce good reasoning models. سيتوقف هذا بسرعة عن أن يكون صحيحًا حيث يتحرك الجميع إلى أعلى منحنى التحجيم على هذه النماذج. “

الآثار المترتبة على نحو كبير بالنسبة لمستقبل تنمية الذكاء الاصطناعي. As companies continue to scale up their models, particularly in the resource-intensive area of reinforcement learning, the field is likely to once again differentiate based on who can invest the most in training and infrastructure. This Suggests that While Deepsek Has Achieved An Impressive Milestone, It Hasn’t Fundamentlly Alver the Long-Term Economics of Advanced Ai Development.

Dario’s deflared Analysis of Deepseek’s Achievements Cuts Through Weeks of Market Speculation to Expose the Actula Economics of Building Advanced AI Systems. for him Blog post

Cross point

Advanced artificial intelligence is still an expensive endeavor, and the exact Amodei examination shows the reason that measuring its real cost requires a full scope of investment. His methodical deconstruction of DeepSeek’s achievements may ultimately prove more significant than the initial announcement that sparked such turbulence in the markets.