Blog Post

How Cutting-Edge Technology is Making AI Smarter and Affordable

January 31, 2025
Written by, Elizabeth Fairley, COO & CDO at Talking Medicines 

With NVIDIA losing over $600 billion in market value today, the focus is all on what caused it—DeepSeek AI. Before jumping to conclusions, here’s why this could be a real game-changer in making advanced AI cheaper and faster—ushering in a new wave of possibilities for businesses, startups, and the economy as a whole. 

Sure, seeing companies like NVIDIA and ASML (Dutch chipmaker) drop in value may spark concerns about the future of AI and receive potential knee-jerk reactions from the market. Many probably wonder if this spells trouble for the broader AI industry. But the bigger picture is quite different. This dip is only short-lived, with DeepSeek’s advancements signalling a major shift that benefits the AI industry in the long run. 

With DeepSeek AI providing performance rivalling that of Open AI, Google (and other major players) for a fraction of the price paints the picture of a breakthrough- the cost to develop and run cutting-edge AI models, particularly those focused on large language models and reasoning, could drop dramatically with algorithmic improvements. This is a game-changer because it lowers the unit cost of AI deployment. We could, very well, be on the verge of a major trend in AI accessibility that could benefit everyone, especially startups.

RMI – Harnessing the Power of S-Curves – 2022

 

This is where the Innovation S-Curve model comes in. The S-curve illustration, as referenced from RMI’s Report “Harnessing the Power of S-Curves“, depicts how new technologies typically go through three phases: slow adoption, rapid growth, and eventual maturation. In the early stages, the technology is often expensive, and adoption is limited. But as costs fall (as we’re seeing with DeepSeek AI’s breakthrough), adoption accelerates dramatically, as more businesses and industries see the value in using the technology. 

Here’s the critical part: as the cost of developing and deploying AI decreases, we move into the “rapid growth” phase of the S-curve. DeepSeek AI’s cost reductions could be just the catalyst that propels AI into this phase. The more affordable and scalable AI becomes, the faster it will be adopted, the more diverse the use cases will be and the more open-source they are. From healthcare and education to entertainment and logistics, AI’s application across industries will expand rapidly. 

As more players enter the market, the pace of innovation will only increase, driving faster growth in AI technologies. We’ve seen this happen with other disruptive technologies, and AI is primed to follow a similar trajectory. This rapid adoption will fuel the next wave of AI innovation. 

This creates a ripple effect for the development of businesses, start-ups, and investors. Businesses and start-ups aiming to try and achieve the same, opening doors for them. Start-ups, in particular, stand to gain from these advancements as this proves that highly advanced AI performance can be achieved for lower costs. This will only make AI more accessible, accelerating innovation across sectors. Start-ups that are leveraging AI for solving real-world problems just got a major tailwind. With costs lowering and adoption increasing, these companies can scale faster, innovate more, and create new products that were previously economically unfeasible.  

We could be witnessing a new era where AI can be deployed more widely, scaling faster and more affordably. 

The advancements in DeepSeek are undoubtedly exciting, showcasing the potential of AI to revolutionize industries, enhance productivity, and drive innovation. However, as we embrace these developments, we must also remain vigilant about data privacy and ethical concerns. AI models like DeepSeek rely on vast amounts of data, raising questions about how information is collected, stored, and used. Without proper safeguards, there is a risk of sensitive data being misused, leading to privacy breaches or unethical applications. Additionally, the potential for bias and misinformation in AI-generated content highlights the need for transparency and accountability. Responsible development and oversight are essential to ensure that these advancements benefit society without compromising ethical standards. 

For Talking Medicines, the evolution of the AI landscape presents exciting opportunities for us to ultimately drive better outcomes for both patients and industry stakeholders. 

As we integrate cutting-edge AI into our work, we remain mindful of critical concerns such as data privacy, bias, and misinformation. Ensuring data is handled securely and ethically is at the core of what we do, and we continue to prioritize compliance with strict regulatory standards.  

At Talking Medicines, we are committed to harnessing the power of AI responsibly. By balancing innovation with ethical considerations, we can continue to unlock intelligence from unstructured data —driving impact while upholding the highest standards of trust and transparency.

 

References

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