2408221539 checking in on someone else’s surfing routine
2408221539 checking in on someone else’s surfing routine
we will be all developers in the future
As the internet becomes more personalized, how it is navigated and experienced is documented as social media content in 2024. It is like traveling, but through an information landscape. These are the early days of the metaverse, but in 2D. The most popular place to check in is Generative AI. As the applications and LLMs evolve, so too have content and user experiences. Daily news and research paper explainers represent the second generation of AI-related posts. The podcast is the present record of a publishing strategy from the past. It is a case study that Dan Shipper & Every is conducting on how Nathaniel Whittemore works on The AI Daily Brief. A traveller trying to learn from another about their tools and the guides they are known for.
Social media content creation is the update of the moment to leverage your digital consumption. Process all the different streams you subscribe to and make something with it. As everything is personalized, it is never possible to directly emulate a workflow, but take in bits that you can reuse to keep your feeds running. The internet is no longer browsed from a search engine but through information services and aggregators. Perplexity, to point out, is search machine-summarized based on your prompts; therefore, the results are never generic. No two questions can have the same answers—at least theoretically.
Any popular online project is always a collective; thus, it's important to consider that more than one person is involved. Generative AI increases both the speeds of consumption and creation. There is also a tendency to follow creators instead of ideas, but that too can change. As we get a glimpse here, there is a dependency on platforms and the trends which are extended. X, previously Twitter, is now better than before as a place to keep track of conversations and therefore build a view of the world. Just like travel is not free, the internet today is also not free—your personal view comes at the price of a subscription service.
Knowledge domains in the past were very siloed with networks; today, it is one blurry mix. Defining a discipline is difficult. Google makes everyone a researcher, social media makes everyone a creator, and generative AI makes everyone a developer. Technology, to reiterate, is not making your productivity increase by default but only subject to additional skills learned. Reference to Excel is one of the better examples I have come across explaining what is possible with generative AI. It is relatively easy to use for a beginner, but the more advanced your skills, the broader the type of output possible with the program.
References & Links
How a Top Podcaster Rides the AI Wave - Ep. 28 with Nathaniel Whittemore [Podcast]
how he curates information with X bookmarks, Google News, news aggregator Feedly, and research tool Perplexity; the workflow that helps him record and produce two daily podcasts; and why he thinks optimizing your processes with AI remains one of its most underrated applications.
How A Writing Pro Uses ChatGPT for Reading, Writing, and SEO - Ep. 2 with Nat Eliason [Podcast]
Inside the Mind of an AI Researcher: ChatGPT and Notion AI Experiments - Ep. 3 with Linus Lee [Podcast]
How David Perell Uses ChatGPT to Write for Millions - Ep. 6 with David Perell [Podcast]
How to Find Your Next Big Idea Hiding on the Internet - Ep. 10 with Steph Smith [Podcast]
Take Your Business From Zero to One With AI - Ep. 16 with Nicholas Thorne [Podcast]
Everything We Teach at YCombinator in 10 Minutes [Presentation]
Artificial Creativity. How AI teaches us to distinguish between humans, art, and industry [Essay]
As far as industry is concerned, getting rid of people and replacing them with AI is the business opportunity. That’s happening on all levels of the AI phenomenon. AI is the last gasp of a dying digital hype cycle. The ultimate meta. Just as the stock market goes “meta” on itself with derivatives and derivatives of derivatives, digital businesses level up into abstraction as a substitute for providing any real value. Web 1 (the dotcom boom) becomes Web 2 (the social media boom) becomes Web 3 (some combination of crypto and virtual reality). When all of those fail, we get AI which is supposed to turn the entirety of the internet into its content as it churns out some new meta-version of digital industrialism that can create exponential growth.
But every modern business model is depending on the same old industrial age premise of making money by getting rid of people, or at least people with skills. That’s what the assembly line was for: get rid of skilled craftspeople, and create a factory system where unskilled, low-paid workers can be trained in minutes and replaced just as fast if they get pesky or try to organize. Business plans for digital businesses only succeed in getting venture capital if they can prove they don’t need human workers in order to scale infinitely. AI offers that possibility.
Wikipedia's known unknowns. An analysis of Wikipedia entries reveals the world's knowledge deserts – which may provide a second wave of activity for the online encyclopaedia [Essay]
Practical tips for retrieval-augmented generation (RAG). Retrieval-augmented generation (RAG) is one of the best (and easiest) ways to specialize an LLM over your own data, but successfully applying RAG in practice involves more than just stitching together pretrained models. [Concept]
Simple implementation: We can create a minimal RAG pipeline using a pretrained embedding model and LLM by:
Separating the knowledge base into fixed-size chunks.
Vectorizing each chunk with an embedding model.
Vectorizing the input/query at inference time and using vector search to find relevant chunks.
Adding relevant chunks into the LLM’s prompt.
Understanding AI Agents: The Three Main Components – Conversation, Chain, and Agent [Article]
The conversation component is the interface through which AI agents communicate with users or other systems.
The chain component, also known as the workflow organizer, structures the actions and decisions an AI agent undertakes to achieve its objectives.
The agent component is the core of an AI system, embodying the autonomous entity that perceives, decides, and acts.
Can we please stop talking about replacing employees with AI? [Article]
OpenAI’s DALL-E 3-Like AI For Free, Forever! [Video]
blackforestlabs.ai [Application]
I Easily Write 50 Articles in a Month Using These 5 Powerful AI Tools. 2 Articles Per Day is a Piece of Cake [Guide]
Mastering Prompting Techniques in the Era of Language Models [Guide]
The Art of the Prompt: A Look at 26 Prompting Principles [List]
Nine Categories of Innovation-Driven Prompt Engineering [List]
Exploration and Ideation
Assumption Validation and Risk Assessment
Strategic Planning and Decision Making
Scenario Analysis and Forecasting
Innovation Execution and Implementation
Customer and Market Insights
Organizational Change and Culture
Technology and Capability Development
Competitive Analysis and Positioning
How to Challenge Your Own Analysis So Others Won’t. Master the art of sanity checks to level up the quality of your work [Workflow]
By routinely applying “sanity checks” to your work, you can proactively identify the weak spots and ensure the result makes sense before you share it with a broader audience.
What sanity checks are and why they matter
How sanity checks are different from how most people check their work
How to do a sanity check
How to use sanity checks to increase your credibility
How to use AI to sanity check your work for you
You Guys Have No Idea Just How Much People Hate Generative AI [Essay]
The great and justified rage over using AI to automate the arts. Bosses are using AI to cut corners and kill jobs in gaming, and gamers, workers, and fans are outraged. The reason why is simple. [Essay]
Understanding the real threat generative AI poses to our jobs. There will be no robot jobs apocalypse, but there's still plenty to worry about. How will generative AI impact our jobs? [Essay]
The consequences of generative AI for online knowledge communities [Paper]
The most powerful takedowns of generative AI, from those who know its impacts best. It's knives out for AI: Engineers, artists, educators and other workers are raising the alarm more loudly than ever before. Here are 8 of their must-read broadsides against the tech. [Essay]
AI and the Productivity Paradox [Video]
AI-induced creativity and the novelty dilemma looming over architectural design [Article]
Where Does AI Go From Here? How Today's AI Tools Rank in Usage — And What Comes Next [Essay]
Introducing Spatial Subscriptions and Premium Features for Creators and Businesses [Service]
Floor796 [Project]
Isometric Projection in Game Development. Playing isometric games is super fun, but understanding the theory behind isometric projection is also extremely important for any beginner game developer. Programming isometric worlds is a huge topic, so I'll try to be as beginner-friendly as possible and cover the basics we need to learn how isometric projection is used in game development! [Essay]
The Internet, That Friend I Used to Know. The prelude to an unprecedented digital exodus [Essay]
By Sunday, all of the gold, silver and bronze medals will have been awarded, and that’ll be it for the Paris Games. The athletes will head back to training, and the eyes of the world will turn to something else. How Olympians get paid, New York Times Morning Briefing by Justin Porter dated 2024-08-09 08:08.