Talking the Future of Tech
Reference: en.wikipedia.org/wiki/Pebble-bed_reactor
Do nuclear power and a potential renaissance in nuclear power, driven by the voracious power demands for data centers, have the potential of becoming accepted, local and an economic boom for communities? If you’re scratching your head thinking, no way, maybe this conversation will change your mind. Enjoy!
Transcript: otter.ai/u/yUJapxBhVAhGnPUKgJ…?utm_source=copy_url
In this episode, we dive deep into the emerging world of building and training small language models. We’ll discuss the benefits, risks, and challenges companies face as they work to create more targeted and efficient AI models. From managing hardware and power requirements to ensuring data privacy and governance, we’ll cover the key considerations for enterprises looking to leverage the power of small language models. Join us as we unpack this fascinating topic and consider the implications for the future of AI and infrastructure operations.
Transcript otter.ai/u/xJ5T-x70WUFQ55ZAsRQr57q6zwE
Reference: www.composabl.com/
We dive into AI, manufacturing and how to improve manufacturing outcomes by better analyzing data.
If you are interested in manufacturing or advanced applications of AI and digital twins – which is where we create accurate representations of physical items – this episode will hit all of your favorite topics!
Transcript: otter.ai/u/xNB0GZQXB4hQMly991…?utm_source=copy_url
We discuss the impact AI and data sovereignty data protection will have on platforms, consolidated management of your data like in Office by Microsoft or Google, on premises, and systems. This includes a whole bunch of data that you will want to use to train AI models to improve your day to day operations, but you probably don’t want a lot of vendors pulling that data apart and transiting it. We have a fascinating discussion about how the market is impacting these forces.
Transcript: otter.ai/u/gpyotjoYz5ev-1Q2yv…?utm_source=copy_url
Power, electrical power, and how the upcoming trend of AI data centers is intersecting as a load with generation, storage, transportation, Bitcoin mining and mining all use power. These are all highly interconnected in how we use and manage the grid, but are using power in different ways.
Transcript: otter.ai/u/mszdgZE5_TG_H6lywY…?utm_source=copy_url
We dive into data operations in today’s episode! We cover the idea that with all of the work we’re doing in AI and ML data analytics analysis, you actually have to steward your data.
We also cover processes controls, like what we have with DevOps in infrastructure, but with similar types of concepts (governance controls automation) around how your data is flowing in your system.
Transcript: otter.ai/u/pesotDnHCCD5lyPVx7…?utm_source=copy_url
Image by DALL-E
If you haven’t had a chance to join in on our book groups, I strongly recommend you take a look at the upcoming books we are reading! Today we discussed Data Science and Context, which is a relatively academic book by a series of doctors, PhDs, Specter, Norvig, Wiggins and Wing. The book gets into some really fascinating analysis techniques, addressing both the practical and ethical implications of data science applications.
We discuss the biases inherent in the book, the things that are missing and potentially disruptive to the core assumptions of the book. So even if you haven’t read this book, I think you will find the discussion fascinating.
This week I’m keeping our warm up discussion about open AI in the podcast. So you will get about 10 minutes of bonus content before the book group discussion as a warm up and it is very related. Our conversations about what has been going on with open AI, their board and Q* are directly related to the concluding ideas in our discussion about Data Science and Context.
Transcript: otter.ai/u/qYBKNhDBKqaghEaxE-…?utm_source=copy_url
Image: Data Science In Context cover
What incidental, or accidental, surveillance state is being created by all of the video and listening devices that are now embedded in our world?
Today we talk through the ramifications of those networks being in private hands in which companies can actually review, analyze and monetize data from these systems. For example – autonomous vehicle cameras and delivery van cameras. This episode discusses the ramifications of this example and more.
References:
arstechnica.com/tech-policy/2023/…s-invade-privacy/
www.vzbv.de/en/court-prohibits-…ivacy-infringements
last-chance-for-eidas.org/
Transcript: otter.ai/u/NszGAX95R70ydlW_fJ…?utm_source=copy_url
Image by Dall-e prompt: “1950s era cartoon of an autonomous car with a lot of cameras spying on people”
How do we limit and regulate LLMs and AI? We approach this at multiple angles and look through what it’s like to regulate this type of technology.
If you’re interested in the limits of any technology, and specifically how AI gets regulated, and where we’re likely to impose legislative barriers or restrictions on this, then this will be a fascinating podcast for you.
Transcript: otter.ai/u/8IsFB-H-U3XzpQ751l…?utm_source=copy_url
Photo by Pixabay: www.pexels.com/photo/black-andro…white-book-39584/
Rob’s Hot Take:
In the Cloud 2030 Podcast episode from October 19th, Rob Hirschfeld delves into the topic of limiting large language models (LLMs) in AI and explores the potential legal frameworks for regulating artificial intelligence and technology. The conversation highlights the intriguing idea that Section 230, a core governing principle of the internet that exempts internet service companies from extensive content moderation, could play a pivotal role in shaping technology use. Hirschfeld suggests that changes to Section 230 might serve as a critical component in influencing the control and regulation of emerging technologies like AI. Listeners are encouraged to check out the full October 19th episode for a detailed exploration of these regulatory considerations and can join ongoing discussions at the2030.cloud.
What goes on behind the scenes with AI, and specifically data center infrastructure and hardware?
We discuss broad ranging concerns, opportunities and market blockers around AI. We also address how deeply it can impact innovation companies’ privacy legislation from the frame of hardware and automation.
Today’s discussion leads us to a larger question of what unlocks innovation in general that we will address in future podcasts.
Links: research.aimultiple.com/wp-content/we…kers.png.webp
Transcript: otter.ai/u/3FUaZ3m8JabYLyJZGH…?utm_source=copy_url
Photo by Tim Samuel: www.pexels.com/photo/woman-handf…hy-chips-6697286/