The hottest Innovation Substack posts right now

And their main takeaways
Category
Top Technology Topics

A Moment of Disbelief

The Last Bear Standing • 45 implied HN points • 31 Jan 25
🕹 Technology Innovation
  1. Deepseek has developed new AI models that are very effective and cost much less than competitors. This shows that you can create powerful AI without needing huge resources.
  2. The way AI models are built might change, focusing more on better training methods instead of just adding more hardware. This means companies might need to rethink their strategies.
  3. NVIDIA's stock took a big hit because of the competition from Deepseek. The market didn't react well to the idea that AI could be done more efficiently.

The Big OpenAI Sellout

KERFUFFLE • 15 implied HN points • 06 Aug 25
🕹 Technology Innovation
  1. OpenAI started as a non-profit to create AI for the good of everyone, not just for profit. They wanted to make sure AI benefits all of humanity.
  2. Over time, OpenAI changed its structure and now seems more focused on making money. Many people are worried this goes against their original mission.
  3. A recent open letter, signed by over a thousand experts, questions if OpenAI is still following its founding goals and whether the public has a say in important AI decisions.

✅ AI adoption in public relations limited, so far

Wadds Inc. newsletter • 59 implied HN points • 18 May 23
🕹 Technology Innovation
  1. AI is not being widely used in public relations yet, with many professionals unsure how to apply it. Only a few people in the industry are actively using AI tools.
  2. Most PR practitioners see the potential benefits of AI, like making work easier and more efficient. However, they have yet to change their workflows significantly because of it.
  3. There's a need for PR professionals to learn about AI and its impacts quickly. If they don't, they might fall behind as other industries integrate AI more effectively.

Finding the third way

The Uncertainty Mindset (soon to become tbd) • 59 implied HN points • 31 May 23
📖 Philosophy Innovation
  1. There are two common reactions to uncertainty: one is to act like everything is knowable and try to control it, which can lead to poor decisions. The other is to give up and think that nothing can be done about the unknown, which doesn't help either.
  2. Instead of sticking to those two extremes, there's a better approach. It's important to recognize that not-knowing can lead to new ideas and actions.
  3. We can break down uncertainties into different types. Understanding these helps us figure out how to deal with situations where we don't have all the answers.

Ribbonfarm Studio --> Contraptions

Breaking Smart • 67 implied HN points • 19 Oct 24
🎭️ Culture Innovation
  1. The newsletter is changing its name from Ribbonfarm Studio to Contraptions. This will help give it a clear identity that reflects the topics it covers.
  2. The writer is currently on a break but plans to resume regular writing soon. They are excited about exploring new themes and ideas under the new name.
  3. During the break, the writer is focused on building physical contraptions and enjoying their time off. They want the newsletter to feel fresh and different when they come back.
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Glyphic's Nanopores

ASeq Newsletter • 21 implied HN points • 27 Jun 25
🔬 Science Innovation
  1. Glyphic has a new way to sequence proteins using nanopores, which is exciting for science. They have filed a patent for this method.
  2. They have shared more data with some investors, showing progress beyond what's in the patent.
  3. Despite their advancements, Glyphic hasn't talked much about their technology publicly yet.

What to make of China's 6th gen?

TP’s Substack • 53 implied HN points • 26 Dec 24
🕹 Technology Innovation
  1. China's 6th generation fighter jets may be larger and more powerful than previous models, possibly able to carry more fuel and advanced electronics.
  2. The future of air warfare might rely on a mix of manned aircraft and unmanned combat aerial vehicles (UCAVs), potentially changing the typical roles and payloads expected of fighter jets.
  3. The anticipated design and capabilities of these new jets suggest they will need significant power for advanced technologies, allowing them to perform a variety of missions effectively.

Going Beyond Buffett

What's Important? • 46 implied HN points • 02 Feb 25
💼 Business Innovation
  1. Warren Buffett is aging, and people are wondering who will carry on his legacy. The focus should not only be on who continues his investment success but also on who can embody his wisdom.
  2. The current market is like a fragile ecosystem dominated by familiar players. Instead of just choosing the best investments, we should be looking for more innovative and holistic approaches to business.
  3. To truly thrive in the future, businesses should embrace new, creative thinking that values quality and human experience over just profits. It's about being adaptable and aware, like a hare evading a predator, instead of a predictable stoat.

The Sequence Opinion #470: Open Endedness AI Could be All We Need

TheSequence • 49 implied HN points • 16 Jan 25
🕹 Technology Innovation
  1. Open-Endedness AI focuses on creating systems that can learn and adapt over time, rather than just completing specific tasks. This allows AI to innovate and find new solutions continuously.
  2. This new approach to AI research aims for something called artificial general intelligence (AGI), which means AI that can perform a wide range of tasks like a human can. It's a big step towards smarter technology.
  3. However, developing Open-Endedness AI comes with challenges. Researchers must find ways to ensure these systems can learn effectively without becoming unreliable or out of control.

The Paradox of Progress: Trying to Predict Impact Often Prevents the Highest Impact

The Good Science Project • 55 implied HN points • 13 Dec 24
🔬 Science Innovation
  1. Predicting the impact of scientific research often stifles creativity and innovation. Instead of following strict guidelines, we should be open to unexpected paths that can lead to breakthroughs.
  2. Today's funding systems are overly cautious and focus on safe, predictable outcomes. This conservatism can prevent transformative ideas from getting the support they need.
  3. To encourage real progress, we need to embrace uncertainty and risk. Funding should support talented researchers and bold ideas, even when the results are uncertain.

The Man-Made Miracle of SpaceX

Common Sense with Bari Weiss • 125 implied HN points • 18 Mar 24
🕹 Technology Innovation
  1. SpaceX follows a strategy of learning from failures to achieve success, as seen from their history with Falcon rockets.
  2. SpaceX's Starship program has promising advancements like successful stage separation, in-orbit fuel transfers, and potential for deep space missions.
  3. SpaceX's success and profitability are driven by innovations like reusable rockets and the Starlink satellite constellation, reshaping the space industry.

To The Metaverse and Beyond...

Holodoxa • 59 implied HN points • 09 Mar 23
🕹 Technology Innovation
  1. Matthew Ball defines the metaverse as an interconnected network of 3D virtual worlds that will revolutionize online experiences.
  2. The metaverse will require new technologies like cloud computing and AI, and pose governance challenges around privacy and competition.
  3. Ball's insights suggest the metaverse will impact education and various sectors, but technical obstacles need to be overcome first.

A few more thoughts on the future of documents

Sunday Letters • 39 implied HN points • 13 Aug 23
🕹 Technology Innovation
  1. Documents are changing from fixed structures to more flexible, interactive ideas. They should represent complex topics in a way that you can explore various aspects of them easily.
  2. AI can help us create better models for understanding and interacting with information. It's like upgrading from simple numbers to more advanced ways of thinking.
  3. In the future, documents will need to allow for meaningful interactions, not just static content. It'll feel outdated if you can't engage with documents in a dynamic way.

Big firms have different incentives

New Things Under the Sun • 192 implied HN points • 24 Aug 23
💼 Business Innovation
  1. Large firms conduct R&D at the same rate as small firms, but they may focus more on process innovations rather than product innovations.
  2. The cost spreading advantage incentivizes larger firms to focus on process innovation, spreading costs over multiple products.
  3. Larger firms may be less inclined to engage in product innovation due to the replacement effect, potentially competing against their own existing products.

A Radical Approach to Handle Your Mistakes

Ruben Ugarte's Growth Needle™ • 19 implied HN points • 23 Jan 24
💼 Business Innovation
  1. Volunteering mistakes can lead to safety improvements. In aviation, encouraging staff to report errors has made flying much safer over the years.
  2. Boeing's decline from an innovator to a company facing serious issues shows the consequences of neglecting quality and safety.
  3. The airline industry adopted new practices that prioritized transparency, leading to a safer environment for both passengers and employees.

An Oral History Interview with ARIA CEO Ilan Gur

The Good Science Project • 22 implied HN points • 13 Jun 25
🔬 Science Innovation
  1. ARIA aims to fund bold projects that create entirely new technologies and industries, not just improve existing ones. They want to be catalysts for major shifts in science and technology.
  2. The role of program directors at ARIA is crucial. They are chosen for their unique visions and are encouraged to pursue high-risk, innovative ideas, even if those ideas face skepticism from others.
  3. Funding is focused on exploring 'opportunity spaces' rather than specific projects. ARIA believes in investing in diverse approaches to find breakthrough solutions, allowing them to adapt and pivot based on what they learn.

The Sequence Opinion #465: Agentic AI and Darwinism

TheSequence • 49 implied HN points • 09 Jan 25
🕹 Technology Innovation
  1. Open-Endedness AI aims to create systems that can learn and adapt over time, not just complete specific tasks. This means AI can continue growing and improving rather than being limited to set goals.
  2. This new approach could allow AI to generate new ideas and solutions continuously, mirroring how evolution works in nature. It's like giving AI the tools to invent and innovate on its own.
  3. There are still challenges in making Open-Endedness AI a reality, including figuring out how to allow machines to learn effectively over long periods. It's an exciting area, but we have a lot to figure out.

Who Will Be the Japan of the AI Era?

European Straits • 40 implied HN points • 12 Feb 25
💼 Business Innovation
  1. Countries or regions that can best adapt their institutions to support AI technology will be the leaders in the AI era, similar to how Japan led in manufacturing with its innovative practices.
  2. Lean production showcased that the real breakthroughs come from rethinking how to organize and manage work rather than solely relying on new technologies. AI has the potential to do the same in knowledge work today.
  3. Successful integration of AI will require cooperation across entire supply chains, not just within individual companies, similar to how Japanese companies thrived through partnerships and collaboration.

The MechaHitler Reich

The Cosmopolitan Globalist • 13 implied HN points • 18 Aug 25
🕹 Technology Innovation
  1. Elon Musk believes merging humans and AI is essential for our survival. He sees it as a way to enhance human capabilities and cope with the challenges posed by advanced AI.
  2. Musk has faced difficulties convincing others about the risks of AI and feels that traditional regulation and oversight are too slow to keep up with fast-moving technology.
  3. He has created a vast system combining his companies to dominate the AI landscape, believing this control will help ensure a safer future for humanity.

The Sequence Chat: The Transition that Changes Everything. From Pretraining to Post-Training in Foundation Models

TheSequence • 56 implied HN points • 04 Dec 24
🕹 Technology Innovation
  1. The transition from pretraining to post-training in AI models is a big deal. This change helps improve how AI can reason and learn from data.
  2. New models like DeepSeek's R1 and Alibaba's QwQ are now using this transition to become smarter and more effective. They can solve complex problems better than before.
  3. The shift is moving away from old methods like reinforcement learning with human feedback. Instead, there are new ways being developed that promise to make AI work even better.

Kuration #282 Week Recap

KURATION • 19 implied HN points • 21 Jan 24
🕹 Technology Innovation
  1. Kuration presents top tech and media headlines from the past week.
  2. The newsletter includes links to articles about Apple, Google, TikTok, Samsung, Amazon, and more.
  3. Readers can catch up on the latest news and trends in the technology and media industries.

Oxford's Legal Action Against MGI... Again.

ASeq Newsletter • 14 implied HN points • 14 Aug 25
🕹 Technology Innovation
  1. Oxford University is taking legal action against MGI over a nanopore sequencer, but their attempts have seen several ups and downs in different countries.
  2. Initially, Oxford sought materials from MGI, but a judge described this as a fishing expedition, suggesting they lacked solid evidence.
  3. There seems to be confusion as Oxford dropped their cases in the US and UK but is now pursuing something in Australia.

6 thought on "Elon Musk" by Walter Isaacson 

SatPost by Trung Phan • 180 implied HN points • 16 Sep 23
🕹 Technology Innovation
  1. Isaacson's approach to biographies is chronological, emphasizing development over time.
  2. Reading biographies like Isaacson's is about learning from others' lives, not necessarily agreeing with all their choices.
  3. Elon Musk's management style involves intense focus, urgency, and a hands-on approach across his companies.

Who Gets to Compute?

Technically Optimistic • 19 implied HN points • 19 Jan 24
🕹 Technology Innovation
  1. The barrier to training large language models (LLMs) has been a challenge due to the high cost of resources like talent, data, power, and computing; this could lead to a situation where only big tech companies control AI, but there's hope for more diversity with smaller models.
  2. Direct Preference Optimization (DPO) is a potential game-changer in training LLMs as it skips the need for a costly reward model, reducing the barrier to entry for creating new models and potentially allowing for more diverse players in AI development.
  3. While DPO may make training large language models more accessible and less costly, it skips an important step involving human feedback that helps iron out biases and improve understanding of how these systems work, possibly hindering explainability efforts.

Finding the way in

Sunday Letters • 59 implied HN points • 23 Apr 23
🕹 Technology Innovation
  1. Building products means you will make mistakes, but listening to users helps you learn what works. If a product isn't useful, people won't care about it.
  2. Incumbent companies can be tough competition for startups. Sometimes, it's better to target smaller, underserved groups that bigger companies ignore.
  3. Being a startup has its own strengths. You can focus on specific needs and spaces that might grow into a big opportunity over time.

The Unomr Serial Nanopore

ASeq Newsletter • 21 implied HN points • 16 Jun 25
🕹 Technology Innovation
  1. Unomr is a new company from ETH Zurich looking to raise between 2 to 3 million dollars. They have over 1 million dollars in grant funding so far.
  2. The company is developing a platform called 'serial nanopore' which seems to be focused on protein sequencing.
  3. Details on their technology are scarce, but it appears they are working on something innovative in the field of biotechnology.

The Bitter Lesson

Artificial Fintelligence • 20 implied HN points • 26 Jun 25
🕹 Technology Innovation
  1. Over time, methods that use more computing power will usually do better than those that don't. It's important to think about how to use more compute in AI.
  2. In the short term, adding human knowledge can help achieve good results quickly, but it's often not a good long-term strategy. Relying too much on human input can stall advancement.
  3. Real success in AI comes from focusing on general improvements that can scale, rather than chasing quick wins with expert knowledge. This approach is harder but pays off in the long run.

Why Didn't Stanley Kubrick & Arthur C. Clarke Predict The iPad?

1517 Fund • 121 implied HN points • 07 Mar 24
🕹 Technology Innovation
  1. Kubrick and Clarke came close to predicting the iPad in 2001: A Space Odyssey, but paper still played a big role in their vision, showing the challenge of imagining the shift to portable computers.
  2. The prediction of flat screens in 2001 was impressive considering they didn't exist at the time; RCA's pursuit of flat-panel technology likely influenced this foresight.
  3. Despite their brilliance, Kubrick and Clarke didn't fully predict the iPad because they were constrained by the prevalent mainframe computing environment and underestimated the advancements in miniaturization and portable computing.

Everything is broken and that's great

Aliveness Studies • 13 implied HN points • 10 Aug 25
💼 Business Innovation
  1. There's a lot of room for improvement in software companies. Many tools have big problems that smaller teams can solve quickly.
  2. Startups often succeed by fixing what's broken, not by creating entirely new ideas. There's a lot of opportunity in existing markets that need help.
  3. Software engineers are still in demand. The need for better software is high, and with new tools, small teams can make things happen fast.

The Unabridged Ridley-Caplan Exchange

Bet On It • 120 implied HN points • 05 Mar 24
🚌 Education Innovation
  1. Innovation often results from small, incremental improvements rather than sudden bursts of inspiration.
  2. Historically, small countries have led the world in innovation, suggesting that population size doesn't guarantee economic success.
  3. Increasing interconnectedness within large populations can enhance innovation more effectively than just striving for population growth.

How Tech Workers Can Save SF

How the Hell • 184 implied HN points • 18 Aug 23
🎭️ Culture Innovation
  1. SF and California have been experiencing high crime rates.
  2. Tech workers can make a difference by committing public, small crimes.
  3. Privileged tech workers can change public perspective on crime by committing crimes.

Indian IT Spices Up Generative AI with New Recipes

Sector 6 | The Newsletter of AIM • 39 implied HN points • 25 Jun 23
🕹 Technology Innovation
  1. Indian IT companies are actively developing generative AI solutions to tap into new business opportunities. They are innovating and expanding their offerings in this area.
  2. Wipro started its generative AI practice two years ago and is working with various companies to create centers of excellence. They are also collaborating with academic institutions to boost their research.
  3. Partnerships with tech giants like Google Cloud are helping companies like Wipro advance the use of generative AI in enterprises. This supports businesses in adopting these new technologies effectively.

Could language models change language?

The Counterfactual • 119 implied HN points • 22 Jul 22
🕹 Technology Innovation
  1. Language is shaped by how we use it, and machine learning models might influence our language by suggesting words or phrases. Over time, these suggestions could change the way we communicate.
  2. The widespread use of predictive text and language models could either slow down language change by promoting similar expressions, or lead to new and unexpected language innovations.
  3. We could see personalized language models that adapt to individual users, potentially changing how we write and understand language, and encouraging less need for clarity in communication.

Software Development and Fear in The Age of AI

Zakaria’s Substack • 2 HN points • 25 Jul 24
🕹 Technology Innovation
  1. There's a lot of fear about AI taking over jobs in software development, but these fears might be exaggerated. While AI can help speed up some tasks, it still needs engineers to solve unique problems.
  2. Large Language Models (LLMs) like GPT-4 can be helpful for mundane tasks like translating text and generating basic code, but they struggle with complex, unique challenges. Their creative solutions often don't fit specific needs.
  3. Using AI tools can make it easier for solo entrepreneurs to code, allowing them to focus on bigger decisions. Learning to work with AI is a valuable skill in today's software development world.