Today Guy Swann dives deep into everything about the “Apple Intelligence” announcement, which aims to integrate powerful AI capabilities directly into the company’s operating systems. He raises thought-provoking questions about the implications of such a system, particularly regarding privacy and trust in a tech giant like Apple. The episode promises to explore the potential benefits and drawbacks of this groundbreaking AI implementation.
Links to check out:

Ai_023 – The Promise of personal Ai (Link: https://fountain.fm/episode/zyaRbKCfCIPtUgzzmr6d)
Does Apple Have a Recording of You Having Sex (Link: https://tinyurl.com/ydhbcbar)
WWDC 2024 (Link: https://www.youtube.com/watch?v=RXeOiIDNNek)

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“Don’t trust. Verify.” — Unknown

A trend I’ve noticed with Ai, is that it has shifted itself into the middleman position between everyone and the normal surfing of the web. While it may save the user time, could this be disrupting the very traffic that monetizes content on the internet? With this fundamental change in the monetization paradigm, a huge shift is coming to the web. What will it look like, and how should we prepare? Tune in to find out.
 
Links to check out

Descript (Link: https://tinyurl.com/bdhr75jr) 
Pinokio (Link: https://pinokio.computer/) 
ComfyUI and Automatic 1111 (Link: https://tinyurl.com/3c6rc6f8) 
Ollama (Link: https://www.ollama.com/)
Open Web UI (Link: https://docs.openwebui.com/)
Logseq and Obsidian (Link: https://tinyurl.com/yypmkrd2) 
LLaVA Model (Link: https://llava-vl.github.io/) 
Hookmark (Link: https://hookproductivity.com/)

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“Disruptors don’t have to discover something new. They just have to discover a practical use for new discoveries.”- Jay Samit

A very unique dynamic occurs with generative AI. LLM companies are scraping the internet for millions of works belonging to other people, photos, videos and film, forum posts, tutorials, all of this human created content meant to provide value to others in hopes of monetizing the attention, or gaining reputation from that research or creation.But without attribution or sharing of the proceeds, we can recreate, mimic, or even pull that exact content back out of the generative models. What does that mean for AI models? What does this mean for copyright? And is the only solution in the violent hand of the state, or is there a technological or cultural solution to this technological problem?
It can be argued that Open AI has become the ultimate middleman, that never even sends its users to the content that makes its product valuable to begin with? In that sense, is OpenAi a breakthrough…or just a different kind of scam? Don’t miss today’s show.
Links to check out

Eight US newspapers sue ChatGPT-maker OpenAI and Microsoft for copyright infringement Dawkins (Link: https://tinyurl.com/2jywhzts)
The current legal cases against generative AI are just the beginning(Link: https://tinyurl.com/ycpx2f5m)
60% of OpenAI model’s responses contain plagiarism (Link: https://tinyurl.com/avch8dfs)
Is A.I. Art Stealing from Artists? (Link: https://tinyurl.com/mukdju7h) 
Voice Stolen by AI? Scarlett Johansson Sues OpenAI in Groundbreaking Case (Link: https://tinyurl.com/3ckpnwxf) 

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“Overprotecting intellectual property is as harmful as underprotecting it. Creativity is impossible without a rich public domain. Nothing today, likely nothing since we tamed fire, is genuinely new: Culture, like science and technology, grows by accretion, each new creator building on the works of those who came before. Overprotection stifles the very creative forces it’s supposed to nurture.”- Alex Kozinski

Today we explore the deluge of announcements from both OpenAi and Google. With a plethora of Ai features dropping at Google I/O And Chat GPT-4o landing with an ai that can be spoken to like a human, how do we determine the difference between groundbreaking AI tools and mere gimmicks. How do we discern practical applications from overhyped features? Join Guy as he navigates the latest AI developments, asking the critical question: What truly enhances our digital lives and what falls short? 
Links to check out:

Rabbit R1 (Link: https://www.rabbit.tech/rabbit-r1)
Google I/O Announcements: Coverage of the latest features and tools introduced by Google, including the Gemini Pro and video gen models. (Link: https://io.google/2024/)
OpenAI’s GPT-40 Announcement: Insights into the latest generative pre-trained transformer model which emphasizes voice interaction (Link: https://openai.com/index/hello-gpt-4o/)
Satlantis Project (Link: https://satlantis.com/)
Welcome to the World of Audio Computers – Jason Rugolo TED talk (Link: https://tinyurl.com/4zc62nhc)
Nova Project: Focus on a business-oriented AI platform that prioritizes open-source solutions and privacy for handling sensitive data.⁠ (Link: Pending)

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“The Limits of my language means the limits of my world”~ Ludwig Wittgenstein

“We’re basically at a fork in the road. I think that there’s a good chance we go the wrong way and you end up with a situation like China.
We need to build these tools that serve Liberty and not tyranny. And we need to design these systems correctly. And then on top of that, I think, as I pointed out earlier, you know, we have an opportunity to build a better product than the tyrannical systems, you know, now before, before you’re in too deep. So we need to do that so that people aren’t, aren’t lured by that.”

Are we steering towards a future where technology amplifies human potential, or are we drifting into a realm where control overshadows creativity? We are joined by the creator of CASCDR today to delve into a discussion that explores the role of Ai in our future and how we can utilize it to decentralize markets, service provision, and change the structure of productivity in a way that can bring it far closer to us and our needs. What does that future look like, and how do we build to get there?

Links to check out:

⁠Range by David Epstein ⁠(Link: https://davidepstein.com/range/)⁠
CASCDR App⁠ (Link: https://cascdr.vercel.app/)⁠
Where Goo Ideas Come From by Steven Johnson⁠ (Link: https://tinyurl.com/49ec9zaa)
⁠PlebLab⁠ (Link: https://www.pleblab.dev/)
⁠Jupiter Notebook⁠ (Link: https://jupyter.org/)

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How close are we to realizing the dream of personal AI? Dive into the potential of small, efficient AI models that enhance our self-awareness and improve our lives without compromising our privacy. Could these advancements lead us to a future where we not only manage but truly own our data, understanding ourselves better than any corporation could? Join us as we explore the fascinating possibilities of personal AI.

Links to check out

Atomic Habits (Link: https://tinyurl.com/hjcajxc)
Facebook’s LLM transparency tool Hugging Face Demo (Link: https://tinyurl.com/4c9cmzhw)
Clone yourself with Delphi A (Link: https://www.delphi.ai/)
The Cold Start Problem: How to Start and Scale Network Effects (Link: https://tinyurl.com/bdzetyax)
The Innovator’s Dilemma: The Revolutionary Book That Will Change the Way You Do Business (Link: https://tinyurl.com/mt6ca37k)
The Pile (Link: https://pile.eleuther.ai/)

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“The reason why it is so difficult for existing firms to capitalize on disruptive innovations is that their processes and their business model that make them good at the existing business actually make them bad at competing for the disruption.”
~ Clayton M Christenson

How can AI be harnessed to manage and enhance personal and professional digital interactions more effectively? In this episode of “AI Unchained,” explore the essential tools and concepts needed to apply AI in self-hosted environments, navigate the intricacies of vector embeddings, and integrate AI seamlessly into your digital workspace. What modular approaches and AI skills are essential as coding becomes more automated? Dive into these questions and more with host Guy Swan.

Links to check out

⁠Devs Who Can’t Code #1 – Build a To Do App
(Link: https://tinyurl.com/29taj247)
⁠Devs Who Can’t Code #2 – Build a Bitcoin Price Tracker
(Link: https://tinyurl.com/38bw54sy)
⁠Unleashed.chat⁠ (Link: https://unleashed.chat/)
⁠NLTK, SKlearn, RE⁠ (Link: https://tinyurl.com/537h53m8)
⁠LM Studio⁠ (Link: https://lmstudio.ai/)

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⁠[Guest Name] on X⁠ (Link: https://twitter.com/guest)
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⁠Guy on TikTok⁠ (Link: https://www.tiktok.com/@theguyswann)
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In today’s episode of AI Unchained we dive into a plethora of new developments in Ai tailored hardware, the scope of what leaps in performance and capacity we may see in the next year, what it means for open source, how to access your local run Ai from anywhere with the Pear Stack, and yet another major tool in generative Ai that will take story telling to a new level? Join Guy Swan as he unpacks the latest and their profound implications for both developers and users alike.

Links to check out

Nvidia A100 chip (Link: https://tinyurl.com/w2sw7ypr)
Nvidia H100 chip (Link: https://tinyurl.com/bdznducy)
AMD’s MI 300X (Link: https://tinyurl.com/5ay5vm48)
Google Axion Processors/Arm-based CPUs (Link: https://tinyurl.com/jd7chher)
IBM’s AI chips (Link: https://tinyurl.com/y8kjyk8p)
Apple’s AI integration in iOS (Link: https://tinyurl.com/4k8dz7u9)
Panochio tool for web generation (Link: https://pinokio.computer/)
Pinokio application for local hosting of AI tools⁠ (Link: https://docs.pinokio.computer/download/)
LM Studio AI model management (Link: https://lmstudio.ai/)
Keet chat app and the Pear protocol (Link: https://keet.io/)
Mixtral 22B and other models from Hugging Face (Link: https://tinyurl.com/mv67p2uy)
LLM Studio for managing large language models (Link: https://tinyurl.com/3fbactk2)
TorchTune documentation (Link: https://pytorch.org/torchtune/main/)
Mistral AI (Link: https://tinyurl.com/33zjuy9z)
GitHub SWE-agent (Link: https://tinyurl.com/3hjwnv5d)
Holesail (Link: https://holesail.io/)
Tom Davenport on X (Link: https://tinyurl.com/438r9z69)
UdioAI (https://udioai.ai/)

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“As I see it, humanity is at a turning point where we must either embrace a small handful of totalitarian super intelligences or move AI to the edge, allowing a wide diversity of machine intelligences to flourish in cooperation with an equally diverse set of human intelligences, forming a truly decentralized hivemind. Fortunately, there’s mounting evidence that open source models will be the ultimate winners.”
~Hivemind Ventures

Our read from HiveMind Ventures today argues that the future of AI development hinges on embracing open-source models and decentralization to counteract the monopolistic tendencies of large corporations and governments. What if we already have the tools and foundations to create a genuine decentralized hivemind of human and artificial intelligences that change how we organize and progress. What if these tools are right under our nose, today? Would you want to know what they are?

Check out the original article at How (Actually) Open AI Wins. (Link: https://hivemind.vc/ai/)

Links to check out

Replit (Link: https://replit.com/)
Hugging Face (Link: https://huggingface.co/)
Langchain (Link: https://www.langchain.com/)
Mosaic ML (Link: https://tinyurl.com/48u2c4yv)
Nomic AI (Link: https://www.nomic.ai/)

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Today we delve into the leadership upheaval at Stability AI, Apple finally putting their cards on the table, the breadth of tools available for image and video generation, more ways to use LLMs to build micro apps, the release of numerous new models, and highlighting broader trends in the AI industry that may be rising to the surface. What might recent developments in the space reveal about the future of open source and centralized Ai? Are we headed toward a brighter, or much darker future? Find out in today’s show.

Links to check out

Sora video generation (Link: https://tinyurl.com/2tmz8tt9)
RunwayML (Link: https://runwayml.com/)
Pika Labs (Link: https://pikalabs.org/)
Stability Ai (Link: https://stability.ai/)
Fountain.fm (Link: https://fountain.fm/)

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Guy on TikTok (Link: https://www.tiktok.com/@theguyswann)
Guy on YouTube (Link: https://www.youtube.com/@theguyswann)
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