This week on Kettle, the focus is on DeepSeek, a venture that started as a Chinese hedge fund but has significantly impacted the stock Market, nearly wiping out a trillion dollars in value from major companies like Nvidia, Microsoft, and Meta. The conversation centers around DeepSeek’s new AI language models, V3 and R1, raising questions about their effectiveness. Guests Tim Prickett-Morgan from The Next Platform, Tobias Mann, and Iain Thomson from The Register join to discuss the technical aspects and potential shortcomings of these models. Tune in for a lively 20-minute episode featuring insights and humor, available audio-only on various platforms like Apple Podcasts, Spotify, and Amazon.
Kettle: DeepSeek Disrupts AI Landscape
This week, the spotlight is solely on DeepSeek. Initially a hedge fund venture from China, DeepSeek has recently rocked the tech world by wiping nearly a trillion dollars off the stock Market value of giants like Nvidia, Microsoft, and Meta. The key question is: are their V3 and new R1 large language models (LLMs) worth the hype?
In our latest discussion, we dive deep into the functionalities of DeepSeek’s LLMs. While they are touted as groundbreaking, skepticism remains regarding whether they truly deliver on their promises. Notable industry voices like Tim Prickett-Morgan from The Next Platform and Iain Thomson from The Register join us to share their insights and critiques.
If you’re curious about the technology behind DeepSeek, Tim explores its backend in detail, while Tobias Mann offers guidance on running the DeepSeek R1 model locally. Their perspectives add valuable context to the ongoing debate.
Catch our engaging 20-minute episode where we dissect these developments with a mix of technical analysis and light-hearted banter. You can also enjoy our content in audio format, available on platforms like Apple Podcasts, Amazon Music, and Spotify.
Stay informed about the evolving AI landscape and the significant shifts brought on by DeepSeek.
Tags: DeepSeek, AI models, stock Market impact, large language models, tech news, Nvidia, Microsoft, Meta, The Next Platform, The Register.
What is DeepFake technology?
DeepFake technology uses artificial intelligence to create realistic-looking fake videos or audio. It takes real footage and alters it to make it seem like someone did or said something they actually didn’t.
How does DeepFake work?
DeepFake works by using machine learning. It trains on images and videos of a person to mimic their appearance and voice, allowing for the creation of convincing fake content.
Why is DeepFake a concern?
DeepFake can be a concern because it can be used to spread misinformation, create fake news, or damage a person’s reputation. This can lead to serious social and legal issues.
What are some uses of DeepFake?
DeepFake can be used for entertainment, like in movies or video games, but it can also be misused for fraud, revenge, or misinformation campaigns, which raises ethical questions.
How is China involved with DeepFake technology?
China is heavily investing in AI and DeepFake technology. As they develop these tools, there are concerns about how they might be used for surveillance, propaganda, or misinformation both domestically and abroad.
