Good Morning, everyone

Thank you for supporting this publication. This is my primary income and I do my best to help you stay informed and keep you stimulated about AI at the intersection of business, society, technology and the future. The usual time the Newsletter goes out is 05:30 AM EST. However this can vary, more so in the Spring and Summer months.

I want to continue our visual tour of some of my favorite infographics and updates of the AI Index report, as well as other things related to the U.S. labor market, macro, geopolitical, the economy, future of jobs, GenZ trends, and related interests, primarily in infographic form.

To read the first issue of this series, go here.

You Don’t Say </>

The Federal Reserve just put a number on something developers have been experiencing for two years. A new study by Fed economists Leland D. Crane and Paul E. Soto found that employment growth among U.S. programmers dropped roughly 50% after ChatGPT launched in November 2022. Before that, programming-intensive jobs were growing at around 5% annually—well above the overall labor market.

Why Infographics

The Daily Spark by Apollo by Torsten Slok is another of my favorite sources for economic and macro infographics. What you find is not all Economists are honest in their incentives. The bifurcation of young people, post graduate entry level employment and AI really has me worried. It’s not the concerns you find in VC AI reports or Academic instructions with affiliations with BigTech. That’s part of the story I refuse to not tell. Infographics can quickly help orient ourselves among multiple data points that converge across spectrums of tech, economics and the future of jobs.

Because I want to do my best to display balanced coverage including some contrarian and skeptical insights that are purely my own and aligned with my own conceptual frameworks, this format of curation favors that.

Why so Anxious? AI is causing systemic division

AI can destabilize a consumer based economy, weaken democratic values and continue to warp Neo Capitalism, and it looks problematic for social unrest, wealth inequality and general rule of law. So why is that?

What happens if a kind of AI populism rises against the AI revolution? There’s a significant disconnect between Silicon Valley, Washington and the general population and real citizens, consumers and young people on this. Axios had this paragraph that stopped in me in my tracks: (I’m going to start a bit critical and realistic but I’ll eventually get to the AI Index part).

“Half of Americans are more concerned than excited about the use of AI, according to Pew, and Gen Z’s excitement about the technology sits at 22%, according to Gallup.”

It’s not just an AI paradox, it’s a legitimate AI risk that I’ve not seen Think Tanks and AI policy academics report on much. Bottom up consensus on AI is starting to form, and it’s contrary to what a lot of Executives, elites and BigTech lobbying has been suggesting. It’s this National divide in the U.S. with regards to the benefits and risks of AI that most concerns me.

But Something is not Right…

The more exposed we are to an Internet of AI slop (AIS) and even the potential of career ladder disruption, the less happy young people are starting to be with regards to their trust and hope that AI will bring a better world.

There’s a point where digital well-being plummets and the affordability crisis starts to impact youth unemployment and the way a culture sees its future with the prospect of AI. A Generative AI that’s not creating meaningful jobs, opportunities and is clearly weakening democracy. This isn’t a warped kind of AI populism, this is AI impacting the very human condition it’s supposed to be empowering, enhancing and augmenting.

We know that the Trump Administration created Energy Crisis with its attack on Iran with Israel is going to meaningfully increase inflation.

Eight weeks into the 2026 conflict (Operation Epic Fury), the global economic data suggests that the "disinflation" trend seen in early 2026 has been reversed. This should also worry those young graduates who are struggling to find entry level work in their industry because U.S. Administration policies and possibly even AI are pressing down their opportunities to participate in the labor force.

Why are Americans growing weary of AI?

• How Americans view AI is deteriorating rapidly in 2026. Drawing on five years of Pew Research Center surveys - I believe the low consumer sentiment on the economy is seemingly being paired with the AI boom, in a K-shaped economy.

• As of late 2025, 50% of U.S. adults feel more concerned than excited about AI’s increased use in daily life, while only 10% are primarily excited. As journalism is being eroded and VC-media is on the rise, if you follow LinkedIn or Twitter/X you’d think it’s a lot higher than those 10% who are excited. The American internet is no longer reflecting reality to such an extent GenZ are beginning to leave the legacy apps that started the internet.

• The discontent around AI could signal the fall of the legacy U.S. advertising based internet.

• A rise in AI anxiety stems from multiple issues, including degraded work opportunities. 18% of workers now believe it is "very or somewhat likely" their job will be eliminated by AI within the next five years, up from 15% in mid-2025. Anthropic, OpenAI or Microsoft making dire predictions isn’t helping and feels particularly tone dear and particularly harmful to the actual experience of people.

Got to give Tim Cook some Credit for Apple Management

Steve Jobs was a tough act to follow but Tim Cook did as well as anyone could have expected. Let’s give credit where credit is due though, Tim Cook’s legacy is being cemented as one of the most successful corporate stewardships in history. Essentially, Cook transformed Apple from a "disruptive hardware company" into a resilient, $4 trillion global powerhouse. Take a bow.

Tokens > People & Workers

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Good Morning, everyone

While I’m trying my best to post a bit less with AI news saturation happening, some days do…

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Anthropic is in the Zeitgeist, no longer a glorified AI research lab startup. Now a full on product explosion is happening. This is what AI Supremacy in coding models, agentic AI and maybe even reasoning models looks like (revenue growth is staggering). Upgrade.

1. “Anthropic: (in philosophy and cosmology) involving or concerning the existence of human life, especially as a constraint on theories of the universe.

   “anthropic reasoning is only interesting in a scientific sense if it can help us understand how the universe came to be the way it is”

2. (typically of environmental degradation) caused by human beings; anthropogenic.

   “anthropic climate change”

What is even Anthropic?

It’s mid April, 2026. Everywhere I look recently I see articles about Anthropic and its many Claude updates. I get it, Anthropic is making a huge push into Enterprise AI, will go IPO in about six months, and just released a preview of one of the most impressive models we’ve seen called Mythos. Anthropic is surging ahead of OpenAI and it has repercussions on the entire Tech stack, and incumbents. Tech layoffs feel different this year. (Oracle, Disney, Epic Games, Atlassian (look at the stock), Block, Workday, etc…)

Fastest Growing Enterprise AI Company Ever

Anthropic is arguably the fastest-scaling software company ever, with diversified compute on Nvidia GPUs but also Amazon and Google AI chips. It’s the foundational Agentic AI-as-a-Service company of the Generative AI era (2023-2026, so far). Its API benefits from the explosive growth of Cursor and it’s getting a lot more Enterprise customers with contracts over $1 Million dollars.

What is this List?

But since most of my readers are primarily AI Enthusiasts, their product release timeline lately has been a bit daunting and snappy. I wanted to list some of the best article resources and guides I could find on this platform. This is essentially a Friday listicle, mostly around Claude guides. Clicking on one of these links supports some of its top AI navigators, educators, analysts, enthusiasts.

In a staggering window between February and April 2026, Anthropic's run-rate jumped from $14 billion to $30 billion.

This week Anthropic announced their solution to Managed Agents.

Read the Blog

According to Deedy Das, a partner at Menlo Ventures who invest in Anthropic:

“Claude Mythos just obliterated every single benchmark in AI.”

It might take some time for us to get our hands on the model, since they are prioritizing trust and saftey.

Claude’s Good Times Begin

Hilariously it’s turned every AI creator I know into a booster for this company. Instead of simply repeating another guide, I wanted to give you my readers a kind of directory to some of the best content I could find around Claude’s various list of new products.

Remember, Claude Code only became widely available to users by May 22, 2025, not even a year ago.

What are Managed Agents?

Just a small note on the latest product:

Claude Managed Agents is a suite of composable APIs for building and deploying cloud-hosted agents at scale, handling sandboxed code execution, checkpointing, credential management, scoped permissions, and end-to-end tracing for you. These are suitable for businesses of all sizes, but especially large companies.

It's best for workloads that need long-running execution (tasks that run for minutes or hours with multiple tool calls), cloud infrastructure with secure containers and minimal infrastructure.

So that’s my intro and here’s my list: (I will try and be brief but also give you some weekend reading if you want to catch up on your AI skills):

Click the links to learn more. (I try to keep paid articles to a minimum in the below list, for learning purposes)

A Short Claude Learning Directory:

I think if you read and scan through some of these articles, it’s fair value for your time. Keeping up to date with Claude AI in practice is likely a good idea.

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Good Morning,

The year 2026 is in many ways the year of AI datacenter and semiconductor bottlenecks. As Nathan Warren over at Exponential View has noted:

⭐ The Helium Shortage

“The Iran War has creat…

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Audio 25 min 56 Seconds

I’ve been watching the Biden Administration’s export controls closely around AI chips. U.S. exceptionalism in the mid 2020s is taking many forms as experts grapple with China’s response to the various measures and if they have worked or even backfired in some unintended ways as historically has often occurred in hindsight. I say this as President Elect Trump has one week until he enters office on January 20th, 2025 which is also Martin Luther King Jr. Day. This as Trump toys with the idea of giving Elon Musk TikTok’s U.S. operations, as per Bloomberg.

I asked of Futuristic Lawyer to get his take on the history of all of these export controls and trade wars and Trump’s likely impact on them, but a lot has taken place since he wrote the article in December just a few short weeks or days ago.

The Biden administration on January 13th, announced new export restrictions focused on artificial intelligence chips and proprietary neural networks.

• Nvidia was quick to signal their response in a blog posted here.

• As I reported on Semiconductor Things on Thursday, export controls have been ramping up.

• On December 2nd, 2024 the U.S. had already launched its third crackdown in three years on China’s semiconductor industry, curbing exports to 140 companies, including chip equipment maker Naura Technology Group, among other moves.

• Then on January 7th, 2025 The US added several Chinese technology companies, including gaming and social media giant Tencent and battery maker CATL, to a list of businesses it says work with China's military.

📩 Top Posts for December 💎

1. The Robots are coming: Genesis

2. Top AI Tools of 2024

3. How to Grade the Top AI Tools for Students

Read Final Rule on AI Difusion

The Biden administration’s last hurrah is fairly dystopian and ranks foreign countries into three groups with various incentives to try to enhance U.S. national security and economic strength (of America). Nvidia is calling the policy ‘misguided’, Nvidia who will soon make nearly 20% of their revenue from China.

Let’s also point out how this flavor U.S. exceptionalism works:

🟢 No restrictions apply to chip sales to 18 key allies and partners.

🤔 LLMs: Restricting the transfer to non-trusted actors of the model weights for advanced closed-weight (read “duopoly”) models.

🔵 The rule builds on previous regulations that aim to protect U.S. national security, including the October 2022 and October 2023 chip controls.

The rules basically cap shipments of advanced AI processors on both a company and a country basis, covering most of the world in an expansion of trade curbs that have mostly targeted China (and its allies). Trump’s Administration is expected to keep to these rules. According to Bloomberg, these rules have set off a “firestorm in Washington”, with some key tech companies — Nvidia in particular — lobbying fiercely against what they see as an extreme overreach. Nvidia’s stock is suddenly down 10% in the last five days.

The new regulation is meant to keep AI from fueling Beijing's military development, administration officials say. However it’s clearly a position of fear and protectionism where U.S. elites are worried about China’s surprising capabilities in AI, patents, multiple emerging tech disciplines, including space technologies, drone technologies, robotics, biotechnology, quantum computing and so forth (basically all the topics I cover).

Unfortunately this will be part of Biden’s legacy. It carves the world up into friends, neutrals and enemies of the United States with profound geopolitical consequences. If you are part of the lucky 18, these new rules mean they won’t place any restrictions on AI chip sales to 18 allied countries.

• The rules categorize countries for GPU export controls, impacting Nvidia's (and a host of other companies) market.

• Part of these 18 “friends” of U.S. exceptionalism include: The allies without restrictions include 🇦🇺 Australia, 🇧🇪 Belgium, 🇨🇦 Canada, 🇩🇰 Denmark, 🇫🇮 Finland, 🇫🇷 France, 🇩🇪 Germany, 🇮🇪 Ireland, 🇮🇹 Italy, 🇯🇵 Japan, 🇳🇱 the Netherlands, 🇳🇿 New Zealand, 🇳🇴 Norway, 🇰🇷 Republic of Korea, 🇪🇸 Spain, 🇸🇪 Sweden, 🇹🇼 Taiwan (Because of course - TSMC) and the 🇬🇧 United Kingdom.

• If you want to read the entire thing go to the Biden administration's Commerce Department 168-page document of fresh regulations for the US semiconductor industry (I believe it will be available on Wednesday).

The rule will create a new global licensing system for the most advanced AI technology exports. The result might actually push BRIC countries closer together and make them more reliant on China’s own nascent semiconductor industry. It’s a divide-and-conquer sort of policy. There are some notable losers who somehow escape being in the friend-group: Notably 🇮🇱 Israel, 🇵🇹 Portugal, 🇸🇬 Singapore, 🇲🇽 Mexico, 🇲🇾 Malaysia, 🇦🇪 UAE, 🇸🇦 Saudi Arabia, 🇮🇳 India and quite a few others (baffling!).

Finally, the policy does not control open-source models, nor would it be able to, a key consideration. Before implementing the new rules, the Commerce Department will give interested parties 120 days to submit feedback. It’s also super interesting and major news with regards to AI in the global order and policies of U.S. exceptionalism trying to limit other regions who they consider national security rivals namely China, Russia and Iran.

Creating a hierarchy in the world around AI chip and model access to U.S. leadership is highly problematic. It could also substantially disrupt global semiconductor supply-chains while negatively impacting certain regions economically that favors the U.S. (and its allies) to the detriment of others and, is not in the spirit of democratizing AI. National security competition has a dark side.

• Ken Glueck, Executive Vice President of Oracle, argues that the regulations will create a market opening for PRC companies in most countries. And he’s not wrong.

• Nvidia, Oracle and industry groups say the rules will undermine American competitiveness and hinder innovation, as reported by Axios.

The U.S. with these policies could also be making matters worse and it likely accelerates a Western bloc vs. an Eastern bloc around the AI arms race that is related to technological supremacy of various kinds that could become an existential threat to civilization’s global security. National factors should never be put ahead of global security concerns. I will leave it at that.

• What follows is Tobias’s deep dive into the historical outlines of how we came to this point before a lot of the recent drama occured in the most recent weeks.

Explore the Work of Futurist Lawyer:

Futuristic Lawyer

Making sense of grey areas between law, IT and ethics.

By Tobias Mark Jensen

By (Tobias Mark Jensen), December, 2024.

Introduction

In the weeks leading up to the US Presidential Election, I consumed many excellent critiques of Trump. The one I found most impactful was “We Created a Monster: Trump Was a TV Fantasy Invented for 'The Apprentice” by NBC’s former Chief of Marketing, John D. Miller.

A few weeks before Election Day, Miller issued an unconditional apology in U.S. News & World Report for creating the illusion that Trump was a successful businessperson as part of the marketing campaign for the popular TV show The Apprentice.

“To sell the show, we created the narrative that Trump was a super-successful businessman who lived like royalty. That was the conceit of the show. At the very least, it was a substantial exaggeration; at worst, it created a false narrative by making him seem more successful than he was. In fact, Trump declared business bankruptcy four times before the show went into production, and at least twice more during his 14 seasons hosting.”

Miller, who interacted continuously with Trump throughout the long-running show, characterizes him as “manipulative, yet extraordinarily easy to manipulate”, “thin-skinned”, as having "questionable judgment" and that "he thought he could simply say something over and over and eventually people would believe it”.

“He would say to me, “‘The Apprentice’ – America’s No. 1 TV show.” But it wasn’t. Not that week. Not that season. I had the ratings in front of me. He had seen and heard the ratings, but that didn’t matter. He just kept saying it was the “No. 1 show on television,” even after we corrected him. He repeated it on press tours too, knowing full well it was wrong. He didn’t like being fact-checked back then either.”

Trump’s ability to think he can refute reality by continuously repeating false statements is part of his appeal to voters and what makes him a humoristic and charismatic leader of the free world, without comparison. Trump’s campaign rallies are a curious mix of stand-up comedy routines and a cult leader delivering truths with fierceness and fatherly authority to the hearts of his followers.

Another major part of Trump’s appeal to voters is that he can offer simple solutions to complex problems. Even to extremely complex matters such as foreign trade policy and dealing with China. A word that is frequently brought up during Trump’s rallies is “tariffs”. Trump affectionally calls tariffs “the most beautiful word in the dictionary” and “more beautiful than love”.

Trump considers the import taxes placed on foreign goods and the trade wars he initiated with China as a crowning achievement of his 2017-2021 presidency. To defeat China in the technology arms race that is currently playing out between the two superpowers, Trump’s answer is simple: higher tariffs and export bans. In Trump’s pitch to voters during the 2024 presidential race, he floated the idea of imposing as much as 60% tax on goods exported from China.

The trade war with China has been the most abrupt change in the history of US trade policy and not a particularly successful strategy. As a result of the trade war, the income in both China and the US has declined (albeit with a small margin relative to GDP) and the brunt of the tariffs was carried by consumers through higher prices. That was the conclusion of a comprehensive literature review by the economic researchers Pablo D. Fajgelbaum and Amit K. Khandelwal, “The Economic Impacts of the US–China Trade War“ (2022). See Paul Krugman’s recent comments on Trump’s trade policy here.

In this post, we will try to understand the trade war between the US and China a bit better, and how it may impact the development of AI globally in 2025 and beyond.

• Enjoy our best content for less than $2 a week commitment only.

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Hey Everyone,

Listen on the Go 🎧 15:54

NotebookLM, the Research Assistant from Google Labs has gotten a lot of traffic in recent weeks, and we were all wondering when Audio Overviews might get more choices and customization. Well, we didn’t have to wait long.

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(☝—💎For a limited time get a Yearly sub for under $5 a month✨— ☝).

Note: Most of my articles are now for premium readers, with some unlocking (temporarily) sometimes on Friday or Saturday for all readers.

Google on Thursday updated the audio summarization feature of its AI note-taking and research assistant with a custom instructions option. You can go to the Notebook guide icon, where you can now ask your AI ‘hosts’ to talk about a specific topic or tailor their discussion to a certain audience.

Google chose to improve Audio Overviews and launched a Business paid subscription related called NotebooksLM Business. The company is expected to reveal general availability and pricing details later this year.

NotebookLM went Viral in September

SimilarWeb suggests NotebookLM saw an over 371% increase in its traffic in September to 3.07 million monthly visits, up from 652,181 a month ago. Those aren’t ChatGPT like numbers, but for a Google AI product that’s still a prototype, it’s a lot. But what will Google Labs do with it?

How to use Custom Instructions

1. To customize the chat, open up a notebook in NotebookLM, select “Notebook guide”.

2. Then navigate to the “Deep dive conversation” option.

3. From there, hit “Customize,” and enter instructions that you want your AI hosts to follow. NotebookLM will then generate a conversation based on the directions you’ve provided.

We have written about NotebookLM here and our guide here.

• NotebookLM now works in other languages.

• Until now, Audio Overviews would automatically generate AI conversations from users’ sources that by default were super general and somewhat generic sounding without any ability to personalize the output besides the sources given.

• Background listening: A new feature allows users to listen to the generated audio while continuing to work within the app. This means you can query your sources or explore relevant quotes without interrupting the audio playback, making it easier to multitask.

• Customizing audio summaries may also help reduce hallucination to some extent according to the product people involved in the project.

NotebookLM is branded as a Personalized AI Research Assistant that can be useful for students, researchers and learning about topics.

With custom instructions for Audio overviews (the synthetic podcast): you can experiment with tone, target audience, specific topics, sources, etc.

• OpenAI makes most of its revenue B2C, while Anthropic makes most of its revenue so far B2B.

AI Manifestos are having a Moment

In late September Sam Altman the CEO of OpenAI wrote this Op-ed blog. Copying him with the prefunding ritual was Anthropic’s CEO with a longer Op-ed with the stylized name “Machines of Loving Grace”. OpenAI, Anthropic, Perplexity and others pitch investors with fairly unrealistic valuations looking for sizable funding rounds.

Founded in 2021 by former OpenAI executives, Anthropic has already raised $7.6 Billion mostly from Amazon and Google. The Anthropic Manifesto had shades of Google DeepMind, especially the last bastion of hype in techno-optimism as a movement as it relates to AI in healthcare and biotech.

Axios noted that “writing a manifesto predicting a glorious AI-driven future has become a mandatory ritual for AI leaders.” It’s not a great sign. The 15,000 word essay by Amodei while better than the immature writing of Sam Altman, is a contradiction in terms.

It’s awkward because pushes back on the idea that he’s a “pessimist” or “doomer” by outlining some grandiose claims for the future of AI. As Anthropic hires big-time product people, OpenAI recently copied them with Canvas eerily similar to Anthropic’s popular and functional Projects.

Amodei’s blog post isn’t for the average AI-curious reader, nor is it a convincing roadmap for the future of AGI, it’s not clear who he is trying to convince? Probably investors.

Leave a comment

• People are trying to convince us with social posts that NotebookLM is useful in their work? I’m not buying it. Even as Google search and Google SGEs feels very dated.

Perplexity on pace to Raise another $500 million

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Hey Everyone,

Since late 2022 many of us have experienced AI-news overload. There are however times when we crave news and reading material, or insights into the trending AI papers, models and speed of progress. As things accelerate there is no lack of rundowns, AI summaries and curation. But what’s unique about this year, 2024?

In some ways 2024 is a consolidation period, where we see if Generative AI is able to take the next steps to Agentic AI, more efficient SLMs, Enterprise AI, more feasible business models and a host of other tidbits. Want to read a newsletter for continuous learning about Machine Learning applications, Machine Learning System Design, MLOps, go here.

For the curious, there’s still so much going on.

I ❤️ Like Those Visuals:

CBInsights: AI 100

• I cannot wait for Databricks to go public and IPO in 2025. I recently predicted that they will acquire Cohere in 2027, whom I call the “OpenAI of Canada”.

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💬Introduction for Today🎯

Tuesday April 9th, 2024.

After one of the biggest weeks for Open-source LLM reveals in recent memory, BigTech are still making outrageous promises. Amid sci-fi speculations about the demand for data-centers, what sort of AI or quantum hybrid supercomputers will we be dealing with?

How do you summarize all that’s going on in the constant stream of the State of AI? I think you just do your best to be open to it all. Taking the pulse of the top AI work tools can sometimes be useful. I read an Introduction to LLM Agents on Github I really liked.

I hope you like links, this took me forever to put together.

For the best reader experience, read this on a PC or a web-browser.

Share

Rumour-Mill

• Jony Ive and OpenAI's Sam Altman Seeking Funding for Personal AI Device & reportedly aiming to raise up to $1 billion in funding from the likes of Thrive and Emerson.

• YC’s newest batch have tons of promising AI startups according to early takes by Investors. I’m doing to do deep dive on some of them soon.

• YouTube’s CEO says OpenAI training Sora with its videos would break YouTube’s TOS: terms of service. But ChatGPT and GPT-4 was definately trained on YouTube transcripts. Confusing!

• For AI firms, anything "public" is fair game. But isn’t that just like scraping the internet for profit something we used to frown upon? Earlier last week, The Wall Street Journal reported that AI companies were running into a wall when it comes to gathering high-quality training data.

• As WWDC is just weeks away, we ask, Can Apple catch up in Generative AI in time for WWDC 2024?

• Apparently, Grok 2.0 will be the 2nd model after Claude Opus to beat GPT-4. The rumours on X of course favor Elon Musk himself!

• Why I believe Stability AI will fail, it defaulted on payments to AWS, owed Google Cloud and CoreWeave money

• My favorite read: Time Exclusive: Google Workers Revolt Over $1.2 Billion Contract With Israel.

Top Tools 📺

• Beam: Beam: Better Decisions, Lower Risk, with Multi-Model AI Reasoning.

• Now, Anthropic’s Claude models can be used to build apps that interact with software like Slack, Airtable or Zoom using their APIs. i.e. “Function calling”.

Cool Tool for Mac 🍎

• Omnipilot - In-context AI in every app on Mac, enriched by the app's context. AI is a shortcut away for writing, email & questions. Download. I’m hoping to do a Native Sponsorship with these people, really neat.

The Best in the Music Business ♫

• Suno.AI - a future where anyone can make great music.

Dev Spotlight

• Codium announces Codiumate, a new AI agent that seeks to be Devin for enterprise software development.

• SWE-Agent: A new agent framework from Princeton researchers that scores 12.29% on SWE-bench (right behind Devin’s 13.84%). Github.

• Amazon offers free credits for startups to use AI models including Anthropic.

• Foundation model development cheatsheet

• The Top 100 AI for Work Report by FlexOS.

See more Tool lists.

An Executive Assistant by Email?

• Astra.AI. An executive assistant in your inbox. Give it tasks like research, get replies by Email.

Learn AI with Maven

• Build with AI by Maven - A modern AI curriculum for engineering, data, and product. A lot of AI creators I know are doing courses on Maven now. There are a lot of May, 2024 listings.

• So much to potentially learn if you are serious to pivot into this space.

• To get the rest of my ICYMI AI news keep scrolling.

Reports

• CBInsights: The top AI companies in 2024: AI 100.

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Hey Everyone,

I’ll honestly never forget the moment I heard Heart on my Sleeve. "Heart on My Sleeve" is a song written and produced by TikTok user ghostwriter977, with vocals made to sound like Canadian musicians Drake and The Weeknd through the use of artificial intelligence. So that brings us to our topic for today.

Substack is foremost a place where we celebrate culture, so how is AI impacting the future of music? If we’re after data-driven analyses about the musical trends of yesterday and today, I think it would be hard to beat . Thankfully was ready to explore this topic for us.

Chris is a musician who spends his days working on analytics and personalization at Audiomack, a NYC-based music streaming service with millions of monthly users. 

Can't Get Much Higher

The intersection of music and data

By Chris Dalla Riva

Bio

As a musician and product manager, Chris is uniquely qualified to talk about this topic. Outside of work, he writes Can’t Get Much Higher, a weekly newsletter about the intersection of music and data. His writing has been featured in The Economist and Business Insider, among other publications.'

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, February-March, 2024.

The Day the Music Lied

When the song “Heart on My Sleeve” by Drake & The Weeknd came out in April 2023, it shook the music industry. The industry wasn’t shaken because two of its biggest stars were collaborating. It was shaken because the two pop stars weren’t collaborating. 

“Heart on My Sleeve” was created by a shadowy figure named Ghostwriter, the song getting millions of streams across TikTok, YouTube, and Spotify before Universal Music Group forced platforms to take it down. Ghostwriter used new technology powered by artificial intelligence to closely simulate the voices of both Drake and The Weeknd. Despite the questionable ethics behind the creation of the song, listeners loved it. Here are some posts on Twitter from around the time the song went viral.

• Daily Loud: “this Drake & The Weeknd A.I song is a hit”

• @MeekMill: “A.I generated song Drake ft. The Weeknd - heart on my sleeve via @YouTube this my 5th time banging this and it’s flame…. We need new music from y’all 2”

• @TrungTPhan: “This song is a new collaboration between Drake and The Weeknd. It’s called “Heart On My Sleeve” and is an absolute banger. It’s also completely AI generated.”

• @itroll93: “Heart on my Sleeve is so much better than anything Drake has put out in two years”

Technological upheaval always seems to affect music before other cultural industries. When the file-sharing site Napster was forced to shut down in 2001, for example, Netflix was still a private company mailing DVDs and six years away from launching a video streaming service. In fact, in the same time frame where you went from buying a VHS to buying a DVD in order to watch a movie at home, you also bought vinyl, 8-tracks, cassettes, CDs, MP3s, and a few other things to listen to music at home.

Part of the reason that musical technology is always evolving is due to cost. Making music is dramatically cheaper than making movies. It’s also due to size and complexity. Downloading a song to my phone only takes up about 3 megabytes of space. A television episode is closer to 100 megabytes and a movie is at least 700. 

Because of these factors, along with a few others, artificial intelligence technology will likely disrupt the music industry much sooner than other cultural industries, “Heart on My Sleeve” merely a harbinger of what is to come. But to understand what “Heart on My Sleeve” is a harbinger of, we need to understand how the music industry itself has changed in the last few decades.

Editor’s Picks of the Guest Author

If you are a fan of music, you will enjoy these:

• tHiS is a p0$t ABOUT Song t!tl3s

• Mommy, Why Did You Name Me Doja Cat?

• Why is Everyone Mad at Spotify?

• I Wish Buddy Holly Released More Bad Music

• Listen to My Story 'Bout TV Theme Songs

The Changing Incentives in the Music Industry

What we think of as the modern music industry didn’t exist until the late-1800s when Thomas Edison invented the phonograph. Before that, the music industry was largely focused around sheet music sales and live performance. The phonograph and subsequent improvements made it so that music could be recorded and sold to the public to play again and again. From that point forward, the music industry was fundamentally a product industry, selling music in many different formats to consumers, along with devices to play that music on.

Because of this, the earliest and most successful music labels were partially technology companies. Edison Records invented the wax cylinder. RCA Victor invented the Victrola. Columbia Records invented the LP. Decca Records invented stereo sound. Philips Records invented the cassette. Sony invented the CD. If we look at industry revenues over the past half century, we can see that the products – usually internally invented – that powered the music industry.

Everything changed around the year 2000, though. That’s when industry revenues began to collapse as digital file sharing sites like Napster, Limewire, and Kazaa ballooned in popularity. File sharing and the technology that made it possible, including the world wide web and the MP3, represented a break with the past because they were a disruptive technology that emerged outside of the music industry. The industry’s response to this disruption was twofold. 

First, the music industry kicked off a ton of litigation against both file sharing sites and fans. Second, they turned back to what they know best: selling music in a new format, this time being downloads on digital music stores like iTunes. Even at the height of their powers, digital downloads were no panacea for an industry in trouble. When they peaked at $3.6 billion inflation-adjusted revenue in the United States in 2012, the music industry was generating the least amount of money since the RIAA began tracking in 1973. 

The rise of music streaming in the 2010s finally began to turn things around. Like file sharing, the disruptive technology that unpinned streaming also emerged outside of the music industry. The underlying economics of music streaming were fundamentally different from the model that supported the industry for almost a century. Streaming is about access rather than ownership. Subscribers pay a flat monthly fee for the ability to listen to whatever they want as much as they want.

Streaming has cemented the idea that the music industry no longer generates revenue by selling different musical products to listeners. They make money by licensing intellectual property to various outside entities, the most important of which are streaming services. This fundamental shift was driven by technological innovation, but two other factors also played a role.

• Expansive Copyright Protection: When the modern music industry was born in the early-1900s, copyright protection only applied to songs, not recordings, and lasted for 28 years with an option to extend it an additional 28 years. Today, copyright applies to both songs and recordings and lasts the life of the author plus 70 years.

• Industry Consolidation: The music industry was highly concentrated in the early 1900s. Independent labels emerged in greater number in the middle of the century before conglomeration began again as the century came to a close. Today, three companies – Sony Music Entertainment, Universal Music Group, and Warner Music Group – control a large portion of the world’s most popular music.

All of these factors combined leave us where we are today. Rather than developing the technology that made it possible to market music in different formats, we have three publicly traded companies who make most of their money by licensing huge swaths of intellectual property that they will control for over a century. It’s in this climate that AI technology is going to shape the next generation of  music.

How AI Will Transform the Music Industry in the Near Term

In a recent profile in the New Yorker, Universal Music Group head Lucian Grainge noted while every wave of technology – “From sheet music to upright pianos to big bands and the huge CBS radio network” – was once painted as a threat to the music business, technological improvements have usually been to the benefit of the industry. In the early 1980s, Grainge recalls, samplers and drum machines made it possible for people to make music who “lacked access to instruments, music lessons, and studios.”

Despite the apocalyptic predictions that have emerged around AI and music, I think their marriage will ultimately end up being similar to previous technological waves, generally enhancing rather than harming the creative process. Here are some areas where AI is already beginning to rear its head.

Vocal Impersonation & Translation

When the aforementioned “Heart on My Sleeve” took the internet by storm, its billing as an “AI Hit” was slightly misleading. When most people think of an AI hit, they are imagining some computer program creating a popular song with little human intervention. “Heart on My Sleeve” required tons of human intervention.

“Heart on My Sleeve” was written and produced by a human. The “AI” piece in the phrase “AI Hit” was AI technology trained on the voices of Drake and The Weeknd to make another human sound like those pop stars. This impersonation trend is likely here to stay. In fact, it is part of a longer trend that began with the ability to buy digital simulations of certain guitar tones and studio ambiances.

While many of the impersonations that you find online – like “Heart on My Sleeve” – were done without permission, a wave of firms are trying to bring the idea into the legal realm. Voice Swap AI, for example, allows users to license the voices of notable musicians.

Other producers are also using AI-powered impersonation to translate their music. Lauv, an American artist best known for his hit “I Like Me Better”, used AI technology to build a model of his voice. Later, he had Korean artist Kevin Woo sing his newest song “Love U Like That”. The AI model then transformed Woo’s performance to sound exactly like Lauv, albeit now singing in Korean. These AI-powered voice filters will become commonplace.

Hooky Sessions: Creating Lauv's "Love U Like That (Korean Version)" with AI

Musical Remixes & Reimaginations

One of the most interesting trends in the last few years is the boom in popularity of sped up and slowed down versions of songs. If you’re not familiar, it sounds like exactly what it is. There is a song that people are enjoying. Somebody speeds the song up or slows it down, applies a small bit of processing, and then posts that version to the internet. That modified version can become more popular than the original recording.

AI will likely turbocharge a listener’s ability to adjust the songs they like far beyond small modifications exemplified by the recent speed and reverb trends. Imagine, for example, you are listening to the Guns N’ Roses ballad “Patience”. You wonder to yourself, “What would it sound like if Guns N’ Roses performed ‘Welcome to the Jungle’ in this style?” Unless you could dig up some rendition of the group doing their hard rock classic with acoustic guitars, you’d be out of luck. But with sufficiently advanced AI, the song could likely be reimagined without amplifiers and distortion with the click of a button. 

Though this technology isn’t readily available yet – in fact, most efforts seem to be focused on vocal rather than musical transformation – it will likely be in the realm of possibility in the coming years.

Stem Separation

In 2023, it was announced that The Beatles were releasing their final song, “Now & Then”. This was an interesting piece of news given that two of the group’s members had been dead for decades. The song was made possible by advances in stem separation powered by AI.

In short, John Lennon recorded a demo at his home in 1977 that the remaining members of The Beatles tried to complete in the mid-1990s. The problem was that the demo was very noisy and Lennon’s piano playing sometimes drowned out his voice. Jump forward to today and a neural network was able to extract Lennon’s voice from the demo with incredible clarity, making it possible for Paul McCartney and Ringo Starr – the two living Beatles – to finish the song.

The Beatles - Now And Then (Official Music Video)

While this technology has already become accessible through companies like LaLaL, Deezer, and Serato, it will likely continue to improve and enable a whole slew of new things. For example, we might be able to remix and remaster degraded recordings from decades ago. Furthermore, a producer who is looking to sample a piano from an older recording will be able to extract the sound without hearing the bleed from the other instruments.

Loop Libraries

One of the most important music firms to emerge in the last decade is Splice. Among other things, Splice is a subscription-based library of royalty-free samples and sounds. Scores of popular songs in the last decade use Splice samples.

Most of these Splice samples, whether they be short loops or sound effects, are created by producers who receive upfront payment for the work. In the near term, we will likely see more and more of these sample libraries composed of AI-generated beats. Furthermore, rather than searching for a particular type of sound and then using various filters to try to find something, you will most likely use a text or audio prompt to get an AI to generate the sound you want.

Background Muzak

According to Glimpse, a trends discovery tool, two of the fast growing music-related search terms are various phrasings of “AI music” and “copyright free music”. In the same way that AI technology will transform how producers generate the short loops that they use to make songs, AI technology will also transform how we create entire recordings. When I say “recordings,” I don’t mean those that you hear on your favorite pop radio station, at least not in the short term. I mean those that you hear when you aren’t paying much attention. 

These recordings, sometimes called “muzak” or “functional music,” are the things you’ll hear in the background of a YouTube video or on one of the many study and sleep playlists that populate Spotify. This music is non-descript, almost anonymous, and will almost certainly not be generated by humans in the coming years. Companies like Boomy and Endel are already making headway. In fact, Universal Music Group and Endel announced a strategic partnership in the middle of 2023.

As with much of the AI technology that has emerged recently, the ability for musical AI  technology to work is presupposed on the idea that there is a huge library of songs and sounds that an algorithm can be trained on. With this idea in mind, recall the micro-history of recorded music that I provided. The large majority of the popular music of yesterday and today is owned by three major corporations. Furthermore, the music industry of today makes most of its money by licensing that huge catalog of music that they own. These facts hold the key to how the music industry will face the wave of AI technology that is just beginning to emerge. 

If you want a technology that allows you to perfectly simulate Taylor Swift’s voice, that technology needs access to the Taylor Swift discography. If you want a technology that allows you to prompt the creation of a psychedelic funk reminiscent of The Temptations in the 1970s, that technology needs access to the music of The Temptations and 1970s funk. If you want a technology that allows you to hear a lo-fi version of the Nirvana album Nevermind, that technology needs access to Nevermind and lo-fi music. To make any of this happen, there are two options: the largest music companies need to license their catalogs to a variety of AI firms or those AI firms can roll the dice and use said music without a license under the assumption that they will likely get sued.

And the music industry loves lawsuits! In fact, you could probably write a history of popular music in the last 50 years just focusing on major copyright infringement lawsuits. According to the George Washington University Music Copyright Infringement Resource, music copyright cases that had a judicial opinion entered rose over 200% between the 1990s and the 2010s. This is particularly astounding given that “Relatively few of these disputes go to trial, and fewer still generate published judicial opinions.”

Will the likely onslaught of lawsuits stop the development of AI technology focused on music? If the lawsuits of the 2000s are any indication, probably not. Shutting down Napster did not permanently end music piracy. The thing that ended piracy was the rise of streaming services who properly licensed music to create a better alternative than the illegal options.

In summary, the music industry will likely come to embrace much of this technology as long as AI firms properly license the music catalogs necessary to train their models. This still begs one final question: Is any of this good for music?

Will AI Destroy Music as We Know It?

Up to this point, I’ve been talking as if music and the music business are equivalent. They are not. And it’s worth ruminating on why this is a false equivalence for a moment. Tons of people work in the music industry because they want to listen to, create, and promote great music. But ultimately, the industry’s goal is to make money from that music. While music can be a means to an end, whether that be financial or not, music is also an end in and of itself.

Making and listening to music might be one of the most human activities in existence. No human culture has ever been found that did not make some form of music. We sing songs at birthdays and at funerals. We listen to music packed in crowds and sitting by ourselves. To make music and to enjoy music is to be human.

Much of the AI technology that we have discussed will impact how people make music. If you are sitting in your bedroom and want to use some AI vocal simulator to make yourself sound like Freddie Mercury, that is fine. You almost certainly won’t have legal representatives from the band Queen breaking down your door to stop you. All ways to make music are legitimate.

Any issues you hear related to AI and music are almost always connected to the music business rather than music itself. The concern in this case is the same concern that has been voiced for a century: new technology will push musicians out of work and prevent the next generation of artists from surviving.

I am an optimist when it comes to most musical technology. The advent of recording did not destroy music. Neither did radio or drum machines or autotune or streaming. All of these things changed music and the music business. But musicians are robust and people will never stop making music. That said, there are some concerns we should be looking out for.

• If people can create “new” music from long-dead superstars using AI, will it make it even harder for young artists to grow a fanbase in an already competitive market?

• If you don’t want to license your music or likeness to be part of the training data in an AI model, is there any good way to opt out?

• If you do license your music and likeness to be part of the training data in an AI model, how can we adequately compensate you for what you have provided?

• If listeners have the ability to modify each and every song to their tastes, will people be driven further apart because they have no truly common culture?

These are hard questions. And I don’t have the answers to them. But I am certain that despite the challenges that lay ahead that music will persist. Humans don’t seem to be able to survive without it.

Thanks to Chris for the incredible breakdown of this fascinating topic. You might enjoy reading:

1. How Have One-Hit Wonders Changed Over Time?

2. Recorded Music is a Hoax

3. Learn more about “Can’t get much higher”.

Postscript - is this the Sora of Music?

Editor’s Note

Have you ever tried Suno.AI? A new AI company called Suno can generate entire songs from simple text prompts. Suno’s primary function is to create original music pieces instantly based on the text prompts it receives. The platform initially engaged users through its Discord channel for testing, later expanding its capabilities to a web interface, making AI-generated music more accessible to a wider audience.

Suno is a bit like the Sora of music. Suno crafts a 15-second song snippet, showcasing the platform’s rapid response and the creative potential of AI in music.

Perhaps will one day help us understand tools like Suno AI and others like it better.

Hey Everyone,

Stability AI was an early pioneer, like Inflection AI, whose future is now in serious doubt. Stability is best known for Stable Diffusion, a popular image generation tool that helped kick off tech’s current AI frenzy and a developer fascination with open-source LLMs.

• Now in early 2024, three out of the five researchers who originally created the technology behind Stable Diffusion have left the company recently.

• The former of CEO of Stability AI has stepped down in a cryptic tweet, a few hours after Forbes had reported the news.

A lot has happend around Stability AI recently. I asked of to do a deep dive on the company. However, in the last few a lot of additional events have taken place. So let’s try to unpack all of this.

For me this is very much an obituary or eulogy for an AI startup I was so very excited about back in 2022. What does that suggest about the Generative AI movement? It’s time for some serious questioning and soul-searching.

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The Open-Source LLM movement continues Sans Stability AI

Stability AI like we said last time we covered it just last week, was one of the key early proponents of the open-source LLM movement. The exodus of even more core talent from Stability AI, raises a lot of questions. Forbes has reported on a lot of the more controversial aspects of the CEO’s conduct.

Stability AI always gave mixed signals.

Emad Mostaque has been an eclectic character to say the least, but also a little bit off the rails (see some of his YouTube podcasts to get the gist of what I mean). Stability AI’s own announcement over the changes, doesn’t tell the full story. A little bit of short to midterm history:

• Stability AI has been one of the the UK’s most promising Generative AI startups for the last few years.

• The company's board has now (late March, 2024) appointed chief operating officer Shan Shan Wong and chief technology officer Christian Laforte as interim co-CEOs.

• Stability had explored selling itself as investors pressured management over its financial position.

• Stability also saw significant high-level turnover in the last 18 months including the key person/people who help OpenAI developed ‘Sora’.

• Mostaque, a larger-than-life presence in the AI world, co-founded the startup in 2019 after various roles at hedge funds and crypto projects. His conduct has been under some serious scrutiny including a lawsuit from a former (Cyrus Hodes) cofounder.

• Tensions escalated last year between Stability AI and some of its largest investors, rising to a point where Coatue Management (via Bloomberg) called for Mostaque to step down in a letter to management. Emad “resigning” has only occurred several painful months later.

Emad’s X profile has gone into stealth mode recently I have noticed.

See his X Profile

He has been talking about decentralized AI now, in line with the ideology around his former crypto activities. His work with Peter Diamandis on his podcast Moonshots is in particular, striking to me: (some of the quotes are pretty wild)

Of course the claims suggested that Generative AI is an exponential technology. He also said some pretty wacky things to generate hype for the movement, which in retrospect or in history might sound a bit inflated. That’s always a red flag to me, when CEOs exaggerate. Sam Altman does a similar thing with a serial playbook.

That being said, Stability AI has made a gigantic contribution to the space. And it may now be on “life-support” much like Inflection AI is just a shell of its former self. For example, it may have to sell itself to Hugging Face. Why so much consolidation in the Generative AI space just two years in?

To understand all of this better, let’s go to the guest post by . Tobias is my favorite lawyer who writes about AI, ethics and AI governance among other things.

Futuristic Lawyer

Writing about the intersection of business, law and tech with a focus on social issues.

By Tobias Mark Jensen

Thanks for your contributions Emad Mostaque, one of the most colorful early founders of the Generative AI open-source movement.

By , March, 2024.

Stability AI Deep Dive

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You take a week off, and Sam Altman gets fired. Not as much happens in a week any longer than it used to in mid 2023. We shall try to keep things brief and condensed.

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📢Top News 📺

(Cohere, Anthropic and Inflection among others took advantage of the chaos at OpenAI in November, 2023. )

Anthropic Introducing Claude 2.1

Cohere Launches Comprehensive Fine-Tuning Suite

OpenAI researchers warned board of AI breakthrough ahead of CEO ouster, sources say

Enterprise-focused AI startup Cohere launches demo chatbot Coral and Chat API

OpenAI $86 Billion Thrive-Led Tender to Continue After Altman Returns (The Information, paid scoop)

Inflection announces Inflection-2 Model that has surpassed GPT-3.5

Google DeepMind’s AI Weather Forecaster Handily Beats a Global Standard (Wired)

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xAI will launch ‘Grok’ chatbot this week: Here’s what to expect

ElevenLabs startup: now lets you use AI to change your voice — here’s how to sound like a different person

UK Generative AI startups Stability AI releases its first foundational model: Stable Video Diffusion

Google Lyria: Transforming the future of music creation

Adobe reportedly acquires text-to-video AI platform Rephrase

OpenAI releases ChatGPT with Voice for everyone for free (X post)

Inflection announces Inflection-2 Model that has surpassed GPT-3.5

Nvidia: delays launch of new AI chip for China

Google in talks to invest in AI startup Character.AI

📰Noted Newsletters📬

• The Real Reason Sam Altman was Fired?

• OpenAI & Grand Strategy

• What is OpenAI, Really?

• OpenAI and the Biggest Threat in the History of Humanity

• The interested normie's guide to OpenAI drama

• Give OpenAI's Board Some Time. The Future of AI Could Hinge on It

• ‘Huge egos are in play’: behind the firing and rehiring of OpenAI’s Sam Altman

• OpenAI: The Battle of the Board (Zvi)

• OpenAI DevDay - a pivotal moment for AI

• Copilot is an Incumbent Business Model

• OpenAI, the Complete Story: Corporate Giants, Religious Fanatics, and Chaos in the Heart of Tech

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• Week of October 16th, 2023.

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Marc Andreessen thinks he’s a techno-optimist shark with an enemy-list. He’s also a man of many AI generated ‘manifestos.’

💬Introduction for Today🎯

This week my phone broke, hence the short edition, but I noticed A.I. news is noticeably slower of late. Peak hype is definately several weeks behind us.

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The Techno-Optimist Manifesto, this wouldn’t be news except Generative A.I. funding might take a huge dive sometime in the next eighteen months (a16z)

OpenAI thinks it’s worth $86 Billion with Thrive Capital to lead purchase

OpenAI, which counts Microsoft Corp. as a 49% owner, is led by Chief Executive Officer Sam Altman and President Greg Brockman. At $86 billion, it would leapfrog the likes of Stripe and Chinese online retailer Shein to become one of the world’s most valuable closely held companies, behind Elon Musk’s SpaceX and TikTok parent ByteDance. 

AI Chatbots Can Guess Your Personal Information From What You Type (Wired) - Paper

Inflection’s Chatbot Pi, get’s real-time web access as well

Anthropic reaches 95 more countries - see the list

Google: New ways to get inspired with generative AI in Search

Amazon begins testing humanoid robots in warehouses to ‘free up workers’

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Hey Everyone,

This was for the week of September 18th, 2023 and some of the week of the 25th. This takes me countless hours, so you might want to take a glance.

Let’s see what happend during the last week or two in A.I. I hope you find something to read of interest here.

You can also just skim the link titles and get some general idea if you are pressed for time. You ready for a lot of news packed into a single piece? Let’s go! 🏃 Weekend reading for the serious folk.

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💬Introduction for Today🎯

This week Meta personas go live, Google Gemini is coming and Anthropic got more funding, from Amazon of all people.

📢Top News 📺

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Anthropic AI: Expanding access to safer AI with Amazon (official)

OpenAI: ChatGPT can now search the web in real time (The Verge)

Meta to release AI persona chatbots this week. Meta to Push for Younger Users With New AI Chatbot Characters (WSJ paywalled)

OpenAI: ChatGPT can now see, hear, and speak (official)

FTC and 17 states sue Amazon on antitrust charges

Writers reach tentative deal with studios to end strike after nearly 150 days

Sam Altman wants to make hardware AI now (Ben’s Bites, Quick bites) What? 🤯

🔗Partnership & Announcements🏭

Spotify: Spotify’s AI Voice Translation Pilot Means Your Favorite Podcasters Might Be Heard in Your Native Language (Official)

Generative AI by Getty Images, A New Product, powered by NVIDIA (Official) - More Context (The Verge)

Amazon Claims to Bring Generative A.I. to Assistant Alexa (TechCrunch)

Announcing Microsoft Copilot, your everyday AI companion (official) (see Ben’s Summary)

Snap partners with Microsoft on ads in its ‘My AI’ chatbot feature

Google: YouTube announces new AI-powered tools (official)

OpenAI launches DALL-E 3, it will appear in Bing as well (official)

OpenAI Multi Modal Marketing Claims: ChatGPT can now see, hear, and speak

Anthropic partners with BCG (Sept 14th)

Cloudflare and Meta Collaborate to Make Llama 2 Available Globally

Meta: Facebook and Instagram will soon get a slew of AI-powered creator tools - View Meta Connect live-stream.

McKinsey launches an open-source ecosystem for digital and AI projects

📰Noted Newsletters📬

Nvidia Illumina Acquisition: The AI Foundry for Healthcare – The Hardware of Life (SemiAnalysis)

🤖 Cyborg Workers (Azeem)

Generative AI and intellectual property

How Google taught AI to doubt itself (Platformer)

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Hey Everyone,

This was for the week of September 11th, 2023.

Let’s see what happend during the last week or two in A.I. I hope you find something to read of interest here. You can also just skim the link titles and get some general idea if you are pressed for time. You ready for a lot of links?

a16z

What GenAI web Product consumer trends can we see now in September, 2023?

Here are the top 6 takeaways according to a16z:

1. Most leading products are built from the “ground up” around generative AI

2. ChatGPT has a massive lead, for now… (Character.AI and Pi have momentum, with Gemini coming soon).

3. LLM assistants (like ChatGPT) are dominant, but companionship and creative tools are on the rise (e.g. Pi, Poe as a gateway, character.ai)

4. Early “winners” have emerged, but most product categories are up for grabs

5. Acquisition for top products is entirely organic—and consumers are willing to pay! (i.e. Paid subscriptions)

6. Mobile apps are still emerging as a GenAI platform (the trend is ‘generative’ to ‘interactive’)

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💬Introduction for Today🎯

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How Are Consumers Using Generative AI? (a16z)

Instagram might be getting generative AI... panoramas? (The Verge)

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📢Top News 📺

Meta preps new AI system: WSJ

Stability AI, gunning for a hit, launches an AI-powered music generator (TechCrunch)

Roblox’s new AI chatbot will help you build virtual worlds (The Verge)

Why Japan is building its own version of ChatGPT (reason: English bias)

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