Deepseek’s unconventional approach to collection
In a surprising and unusual movement within Artificial Intelligence (AI) IndustryDeepseek, the AI company that made a splash to allegedly offered a very capable model to a fraction of the cost of US competitors, has announced that it does not actively seek venture capital financing.
Deepseek quotes three primary reasons to avoid venture capital (VC) money. First, they do not want to dilute ownership or lose the company’s control. Second, they fear that investments from Chinese companies can make potential global customers even more skeptical of their platform data secrecy and security. Third, they claim that they simply have not had to collect external financing; So far, Deepseek claims that it relied on gains from their time as a quantum -hedge fund, high flyer, before it swung to AI.
Although it is not uncommon for a company to start or minimize investments outside, Deepseek’s strategy seems illogical given the financial requirements of AI development, especially when you believe that Deepseek’s main product is open source. Running an AI operation is extremely expensive, and even the greatest technical giants in the United States are fighting for make profits from their AI business. This asks the question of how Deepseek manages to keep its business afloat. If they continuously improve their models, costs will only increase. Serving more users will also increase expenses. Without turning a profit or secure outside the capital, they effectively compete to the bottom of their bank account unless they have alternative financing strategies that do not require giving up ownership.
Time will show if this game pays off. Either Deepseek will prove that it can maintain itself through unconventional financing methods, or it will end cash and is forced to rethink their attitude to investments outside.
A force in the AI legislation
This year, hearing calls for more regulation have become rare, especially in high -growing industries. But despite the federal government’s deregulatory attitude so far, AI legislation is increasing at the state level. On just the first three months this year, 838 AI-related bills are currently on the waysurpasses the 742 proposed regulations introduced in 2024.
So why has there been a sudden increase? I would say that there are two important factors behind this. First, AI’s presence in daily life has become impossible to ignore. While AI has been around for decades, it is now more visible and accessible to consumers than ever before. This level of adoption Of course, legislative updates to manage the integrity of the consumer, data security and Ethical problems.
Secondly, the AI regulation provides a political opportunity. Legislators who position themselves as early experts in AI policy will receive prestige and career benefits. Given how new consumer mode AI market is, those who lead the conversation now have a chance to shape future policies and secure key positions in technology committees.
It is worth noting that most of this legislation takes place at the state level. However, the Trump administration has shown some interest in heavy-handed regulation, especially if it could slow down AI -Innovation. If federal legislators decide to act, it can take the form of overall rules at the state level to prevent what industry leaders see as patchwork regulation that suffocates growth. The Vita House’s attitude to AI policy remains unclear, but with the legislative torque building at the state level only increases the pressure for federal measures.
US AI Policy suggestions from Google and Openai
As the deadline on March 15 for submission AI’s policy recommendations to Office of Science and Technology Policy (OSTP) Approach, great technical players like Google (Nasdaq: Googl) and Openai has proposed ideas for shaping US AI landscapes.
Both companies emphasized the need for state aid in several areas. Here are some of the highlights of each proposal.
In the case of AI infrastructure investments, Google and Openai claim that the United States must increase infrastructure and energy resources to support AI model development. In addition, they both recommend that the government begins to adopt AI-powered solutions within federal agencies.
Both proposals also affect regulation; Openai, in particular, warns against a fragmented, state regulatory landscape. The company advocates for federal regulations that exceed AI laws at the state level and claimed that inconsistent state policy can slow down AI-Innovation.
Openai also pushes that the AI models are legally allowed to train on copyrighted material During the doctrine for fair use. This has been a disputed question for them, with Openai already before moods from publications like New York Times over unauthorized data use.
Another important aspect of each proposal was that both companies emphasized that the United States must actively promote its AI strategy on the global stage. They require policies that support us AI companies in international markets while balancing export controls to prevent rivals like China from getting an advantage.
Google submitted a 12-sided proposalWhile Openai provided one 15-sided documents. Whether the Trump administration will ultimately adopt its recommendations remains to be seen. But given how the administration has worked so far and placed a high value on its relationships with the technology industry, there is a strong opportunity that great technology will have significant influence over the final AI action plan.
In order for artificial intelligence (AI) to work properly within the law and thrive on growing challenges, it must integrate a corporate blockchain system that ensures data input quality and ownership – which makes it possible to keep data secure and at the same time guarantee data impossible. Check out COINGEEK’s coverage on this new technology to learn more Why Enterprise Blockchain will be the spine in AI.
Look: Adding the human touch behind AI
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