The hottest AI Substack posts right now

And their main takeaways
Category
Top Technology Topics

Use ChatGPT Team without having your data retained forever

Deploy Securely • 255 implied HN points • 19 Jan 24
🕹 Technology AI
  1. Model training is off by default in ChatGPT Team, an improvement from previous versions.
  2. ChatGPT Team brings customers under OpenAI's business terms of service, offering indemnification against claims.
  3. Enterprise controls in ChatGPT Team are locked behind an upgrade, affecting data retention settings and security measures.

Recruiting Brainfood - Issue 331

Recruiting Brainfood • 452 implied HN points • 12 Feb 23
💼 Business AI
  1. ChatGPT technology is influencing big tech companies like Google and Microsoft to pivot their product strategies.
  2. DEIB initiatives in hiring face challenges, such as politicization in the US, demonstrated by Texas potentially banning diversity measures.
  3. PwC's CEO survey reveals a focus on adapting to change: increasing internal flexibility, upskilling, and external collaboration.

🎇💥 Strike on Iran shows why US doesn't want to lose the AI race

Faster, Please! • 274 implied HN points • 23 Jun 25
🇺🇸 U.S. Politics AI
  1. Keeping up with technology is crucial now. Being behind can mean falling behind in significant areas like defense.
  2. Advanced military tech, like stealth jets and AI, gave a major edge in recent conflicts. This shows how important new tech is in today's warfare.
  3. As AI gets smarter, it could create an even bigger gap in military capabilities. This has people worried about who will lead in future tech.

5 Key Predictions for the Data Industry in 2025

SeattleDataGuy’s Newsletter • 612 implied HN points • 07 Jan 25
🕹 Technology AI
  1. Iceberg will become popular, but not every business will adopt it. Many companies want simpler solutions that fit their needs without needing lots of complicated tools.
  2. SQL isn't going anywhere; it still works well for managing and querying data. People have realized that a bit of order in data is important for getting meaningful insights.
  3. AI use will become more practical, focusing on real-world applications rather than just hype. Companies will find specific tasks to automate using AI, making their workflows more efficient.
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Telepathy.

News Items • 235 implied HN points • 30 Jan 24
🕹 Technology AI
  1. Neuralink is working on implantable computer interfaces for the human brain.
  2. Telepathy, Neuralink's first product, will enable controlling devices through thoughts.
  3. Initial users of Telepathy will be people who have lost limb function.

AI’s Great Infrastructure Boom: Bullwhip or Building the Future?

Gad’s Newsletter • 56 implied HN points • 01 Dec 25
🕹 Technology AI
  1. AI infrastructure investment is skyrocketing, with tech giants investing billions in data centers and chips. This could lead to major changes in how AI is developed and used in the future.
  2. The bullwhip effect is making the supply chain for AI unpredictable, causing spikes in demand that may not match actual needs. This could result in periods of overordering and shortages.
  3. Despite potential oversupply and price drops, the long-term demand for AI technology is expected to be strong. This means the current build-out is more likely part of a lasting change in the tech landscape rather than a temporary bubble.

LAION-5B, Stable Diffusion 1.5, and the Original Sin of Generative AI

Cybernetic Forests • 279 implied HN points • 03 Jan 24
🕹 Technology AI
  1. The article discusses the implications of AI infrastructure and the lack of input from the right experts in the field.
  2. It highlights the presence of concerning content within AI training datasets like LAION-5B, raising ethical issues in generative AI systems.
  3. The author mentions being quoted in a Wired Magazine article about Generative AI in relation to Mickey Mouse, hinting at upcoming content on this topic.

GenAI and LLMs: Insights from TikTok and KPMG

Gradient Flow • 119 implied HN points • 18 Apr 24
🕹 Technology AI
  1. Large enterprises are shifting towards in-house AI application development using foundation models, impacting the industry by enabling cost savings and customization.
  2. AI adoption rates among U.S. businesses are rapidly growing, expected to almost double by Fall 2024, with a focus on technology and development applications.
  3. Companies like TikTok and KPMG are adopting GenAI in different ways – TikTok invests heavily in content creation, while KPMG focuses on integrating AI into audit and advisory services, showcasing diverse applications of GenAI.

AI Roundup 146: Opus Day

Artificial Ignorance • 58 implied HN points • 28 Nov 25
🕹 Technology AI
  1. Anthropic launched a new coding model, Claude Opus 4.5, which is cheaper than its last version and performs well, helping developers save costs.
  2. There is a memory chip shortage affecting tech companies, making electronics more expensive for consumers, as manufacturers focus on producing chips for AI instead of everyday devices.
  3. China is gaining ground in the AI market by releasing open-source models cheaply, while American companies stick to closed systems, which could reshape how information is shared globally.

Charting the Graphical Roadmap to Smarter AI

Gradient Flow • 399 implied HN points • 02 Nov 23
🕹 Technology AI
  1. Knowledge graphs can enhance large language models (LLMs) by providing structured factual knowledge about the world, improving their reasoning abilities and usefulness for real-world applications.
  2. Augmenting pre-training of LLMs with knowledge graphs through techniques like integrating into training objectives and model inputs can create models proficient in language generation and factual knowledge.
  3. Enterprises can leverage their data to enhance LLM applications with knowledge graphs, as tools exist to automatically turn semi-structured data into structured knowledge graphs.

Import AI 343: Humanlike AI; LLaMa 2 protests; the NSA's new AI center

Import AI • 439 implied HN points • 09 Oct 23
🕹 Technology AI
  1. Google DeepMind and 33 labs created a large dataset for training robots, showing that using heterogeneous data and high-capacity models improves robot performance.
  2. Protests have begun against Facebook for releasing AI models that can be easily modified, raising concerns about AI safety becoming a political issue.
  3. Generative image models are displaying human-like qualities in tasks, like shape bias and understanding perceptual illusions, suggesting a convergence between AI systems and humans.

AI news roundup: You see what you want to see

The AI Frontier • 79 implied HN points • 23 May 24
🕹 Technology AI
  1. Recent AI updates have sparked excitement and frustration; everyone interprets them differently, like a Rorschach test.
  2. The improvements in AI tech are impressive, particularly in multimodality, but their impact varies between consumer and enterprise applications.
  3. The AI market is growing rapidly, with hype increasing and many companies looking to innovate, but there are still big questions about the future and how to stay competitive.

The bull case for AI startups

The AI Frontier • 59 implied HN points • 13 Jun 24
🕹 Technology AI
  1. AI startups have a lot of room for innovation, even with big companies investing heavily in AI. There are still many opportunities for new ideas and products.
  2. Startups can take more risks and try out unusual ideas that bigger companies might avoid due to reputation concerns. This freedom can lead to exciting new products.
  3. While big companies have access to a lot of data and resources, startups can be more flexible and connect data from various sources. This can give them an advantage in creating better solutions for customers.

Harmony, melody, and coding with AI

Sunday Letters • 39 implied HN points • 07 Jul 24
🕹 Technology AI
  1. We are experiencing a shift in programming that changes how we interact with code and AI. Just like moving from desktop to cloud, this new way will come with challenges and need new thinking.
  2. Combining traditional coding with AI models is important. It's like writing music where the code provides a solid structure, while AI adds creativity and flexibility.
  3. To succeed in this new environment, programmers should keep learning and adapting, using both past knowledge and new technologies carefully together.

The One and a Half Gemini

Don't Worry About the Vase • 1657 implied HN points • 22 Feb 24
🕹 Technology AI
  1. Gemini 1.5 introduces a breakthrough in long-context understanding by processing up to 1 million tokens, which means improved performance and longer context windows for AI models.
  2. The use of mixture-of-experts architecture in Gemini 1.5, alongside Transformer models, contributes to its overall enhanced performance, potentially giving Google an edge over competitors like GPT-4.
  3. Gemini 1.5 offers opportunities for new and improved applications, such as translation of low-resource languages like Kalamang, providing high-quality translations and enabling various innovative use cases.

Did OpenAI Just Kill Glean?

Enterprise AI Trends • 253 implied HN points • 26 Jun 25
🕹 Technology AI
  1. ChatGPT can now perform 'Deep Research' using private documents from sources like Google Drive and Dropbox. This makes creating reports much easier for users.
  2. The ability to generate reports is significant because a lot of middle managers spend a lot of time on this task. It's a huge time-saver.
  3. This new feature could impact other apps that provide similar research functions, like Glean, making it a competitive landscape for AI applications.

I'm launching the Solo Founders Podcast tomorrow

Texts with Founders • 2 implied HN points • 03 Mar 26
🎙 Podcasts AI
  1. A Solo Founders Podcast launches tomorrow and will feature founders who share concrete, battle-tested lessons. The first episode spotlights a solo founder who scaled from $100K to $1.25M ARR in two weeks by using AI for the majority of the business.
  2. Subscribing before launch helps the podcast rank better, so early subscribers make a real difference. Trailers are available on Spotify, YouTube, and Apple Podcasts if you want a quick preview.
  3. Anyone who subscribes before the launch is invited to a private Zoom AMA about building solo. Subscribe, reply "DONE", and you'll receive the calendar invite.

Enterprise Generative AI Unfolded

Gradient Flow • 439 implied HN points • 27 Jul 23
🕹 Technology AI
  1. Mastering Model Development & Optimization is crucial for building efficient and powerful Generative AI and Large Language Models. Scaling to large datasets, applying model compression strategies, and efficient model training are key aspects.
  2. Customizability & Fine-tuning are essential to adapt pre-existing LLMs to specific business needs. Techniques like fine-tuning and in-context learning help tailor LLMs for unique use cases, such as adjusting speech synthesis models for customized experiences.
  3. Investing in Operational Tooling & Infrastructure, including robust model hosting, orchestration, and maintenance tools, is vital for efficient and real-time deployment of AI systems in enterprises. Tools for logging, tracking, and enhancing LLM outputs ensure quality control and ongoing improvements.

The Sequence Radar #779: The Inference Wars and China’s AI IPO Race

TheSequence • 35 implied HN points • 28 Dec 25
🕹 Technology AI
  1. Nvidia licensed Groq’s LPU technology and brought key Groq leaders onboard, consolidating talent and inference IP to reinforce its lead in inference hardware.
  2. Chinese model labs are shipping frontier models: Zhipu’s GLM 4.7 pushes coding and agentic ‘deep thinking,’ while MiniMax’s M2.1 uses linear attention and MoE to enable a massive 4‑million‑token context window at much lower cost.
  3. Zhipu and MiniMax preparing Hong Kong IPOs shows foundation models are moving from VC-funded research to public, revenue-focused companies, and highlights a split where U.S. scaling is driven by capital and hardware consolidation while China focuses on architectural and economic efficiency.

The Software Engineer with Alzheimer's

In My Tribe • 273 implied HN points • 05 Jun 25
🕹 Technology AI
  1. AI, like Claude, struggles with memory, especially remembering recent conversations. It's important to find ways to manage this limitation to keep projects on track.
  2. Maintaining state is a key challenge for AI development, which affects how well an AI can serve as a personal assistant. This functionality isn't expected to improve quickly.
  3. AI technology can be very useful, and while people may doubt its potential, history shows that dismissing new tech often proves wrong.

5 questions about the "AI opportunities action plan"

Odds and Ends of History • 603 implied HN points • 14 Jan 25
🕹 Technology AI
  1. The AI Opportunities Action Plan is an important government report that aims to guide Britain's approach to artificial intelligence. It has many recommendations that could shape the future of AI in the country.
  2. Keir Starmer, the Prime Minister, is focusing on making Britain a leader in AI technology, highlighting its significance in politics and industry.
  3. There's a need for meaningful questions about AI policy, as many journalists often ask irrelevant questions that miss the key issues. Being informed helps drive better discussions around AI advancements.

Language Agent Tree Search — LATS

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 59 implied HN points • 12 Jun 24
🕹 Technology AI
  1. The LATS framework helps create smarter agents that can reason and make decisions in different situations. It's designed to enhance how language models think and plan.
  2. Using external tools and feedback in the LATS framework makes agents better at solving complex problems. This means they can learn from past experiences and improve their responses over time.
  3. LATS allows agents to explore many possible actions and consider different options before making a choice. This flexibility leads to more thoughtful and helpful interactions.

What Are Companies Doing With Generative AI? A Tale Of 3 Strategies.

High ROI Data Science • 297 implied HN points • 12 Jan 24
🕹 Technology AI
  1. Companies are using Generative AI tools to decrease training times and improve customer service in retail.
  2. Some companies are implementing Generative AI without a clear business problem statement, leading to undefined outcomes.
  3. Retailers like Walmart are strategically using Generative AI to change customer workflows, improve online shopping experiences, and increase revenue.

Data Science Weekly - Issue 536

Data Science Weekly Newsletter • 179 implied HN points • 01 Mar 24
🕹 Technology AI
  1. The DSPy framework makes working with large language models easier by focusing on programming instead of complex prompting techniques. This helps reduce errors and improves usability.
  2. A new sequence model approach shows better performance than traditional Transformers, especially for long data sequences. It also works faster, making it a promising development in the field.
  3. Learning resources like online courses and free books on deep learning and causal ML can help deepen understanding of data science. They provide structured material that is great for both beginners and advanced learners.

Dario Amodei + DeepSeek’s New Burdens

ChinaTalk • 518 implied HN points • 06 Feb 25
🕹 Technology AI
  1. DeepSeek is facing challenges in managing corporate partnerships while maintaining its research-focused culture. They might have to balance getting support from big tech companies with staying true to their values.
  2. As DeepSeek becomes more popular, it risks losing its talented employees to other companies offering better pay. This could change the company's culture and innovation approach.
  3. If DeepSeek forms closer ties with the Chinese government, they could get funding and resources, but it may come with scrutiny and reduced independence. They need to navigate these relationships carefully.

Against AI Doomerism, For AI Progress

Extropic Thoughts • 432 implied HN points • 02 Apr 23
🕹 Technology AI
  1. There is a debate between advancing AI to solve human problems and fearing AI apocalypse.
  2. Calls for pausing AI developments may not be effective and could lead to negative consequences.
  3. Fears of AI causing global disasters may be exaggerated, and caution should be taken in implementing regulations.

This Week in AI Doublespeak

Marcus on AI • 3122 implied HN points • 18 Mar 23
🕹 Technology AI
  1. Tech doublespeak can be compared to political manipulation
  2. AI models claiming to reason may not always provide valid conclusions
  3. Companies may not align actions with stated commitments regarding AI ethics

MCP Is Just an API

The API Changelog • 9 implied HN points • 06 Feb 26
🕹 Technology AI
  1. MCP is basically another kind of API that lets LLMs access live data and perform real-time actions, making agents more useful.
  2. The spec is evolving fast and now has major industry backing, which pushes it toward becoming a reliable standard. That rapid change also creates adoption, versioning, and security gaps that need tooling, best practices, and governance.
  3. API product teams and existing OpenAPI practices are well placed to manage MCPs, since good API design leads to better MCP servers and the ecosystem will need product-focused governance, gateways, and UI/app support.

Clouded Judgement 1.30.26 - Software is Dead...Again!

Clouded Judgement • 15 implied HN points • 30 Jan 26
💼 Business AI
  1. SaaS valuations are at decade lows — the median NTM revenue multiple is about 4.1x and FCF multiples have fallen sharply while growth rates are also weak (median NTM growth ~12%).
  2. Investor confidence in the SaaS business model has been shaken because AI and the much lower marginal cost to build software increase competition, threaten retention, and raise the chance that some companies have little or no terminal value.
  3. Markets will likely only recover if companies show stable retention and resilient cash flows despite AI challengers over multiple quarters, and early reports (e.g., ServiceNow) haven’t yet shown widespread retention declines.

Gaussian Pop: 14 Theses

Cybernetic Forests • 119 implied HN points • 14 Apr 24
🎨 Art & Illustration AI
  1. Gaussian Pop music is generated by AI models prompted by user searches, aimed to reduce streaming service costs and drive profits through listener engagement.
  2. Gaussian Pop creates music that satisfies the urge to consume quickly and easily, tailored for inattentiveness and quick skips.
  3. The rise of Gaussian Pop represents a shift in music consumption towards AI-generated content, leading to concerns about economic impacts on musicians and the potential alienation of shared music experiences.

Weekly Dose of Optimism #153

Not Boring by Packy McCormick • 205 implied HN points • 18 Jul 25
🕹 Technology AI
  1. There are massive investments in AI infrastructure, mainly in Pennsylvania, with companies like Google and Blackstone pledging billions to build data centers. This investment is expected to create many jobs and boost the local economy.
  2. Meta is working on building a huge data center called Hyperion, which will provide lots of power for AI development. They plan to invest around $70 billion in AI this year, which could lead to significant advancements in their products.
  3. A new study shows that a technique called three-person IVF can produce healthy children by combining DNA from three people to prevent genetic diseases. This could change how families with these conditions approach reproduction.

🎭✨ Ben Affleck’s wise words on AI

Faster, Please! • 731 implied HN points • 18 Nov 24
🕹 Technology AI
  1. New technology, like AI, can help reduce costs. This can make it easier for more people to access entertainment and creative content.
  2. There's a common fear that robots will take over jobs, but it's important to understand how technology can create new opportunities instead.
  3. Adapting to new technologies can lead to a demand for different skills. Learning and evolving with technology is key to staying relevant in the job market.