Original author: Y Combinator
Original translation: TechFlow
The golden age of construction
There has never been a better time to be a builder. We just witnessed an amazing scene: a giant robot called Chopsticks snatched a falling skyscraper from the air with pinpoint accuracy. This is not only a technological miracle, but also a huge leap in our ability to build. Artificial intelligence (AI) is changing the way we work at an unprecedented rate, and for builders in particular, AI is having a profound impact. It can be said that we are entering a golden age of construction, which provides us with a rare opportunity to create things that can truly change our country for the better. Here are some of the innovations we think are particularly worth paying attention to and exploring in this golden age.
Government Software
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Author: Harj Taggar
Selling software to the government has a notoriously high barrier to entry, and most entrepreneurs won’t even consider entering the field. But if you can crack it, the rewards can be huge. For example, Palantir is one of the few startups that has successfully entered this market, and its current market value is as high as $125 billion.
Now may be a particularly good time to try. With fiscal deficits high, governments are in urgent need of reducing spending and improving efficiency to ease the pressure. At the same time, the rapid development of artificial intelligence technology has made it possible to automate many administrative tasks that cost governments billions of dollars each year.
Combining these two points, developing AI-based software to help governments automate work can not only reduce expenses but also improve efficiency. In particular, large language models (LLMs) excel in handling repetitive administrative tasks such as filling out forms, reviewing applications, or summarizing documents. As users of government services, we all benefit from more efficient services, such as no more long lines at the DMV.
While government might sound like a less sexy area to start a business in, if you’re willing to dig deeper, we’d love to hear your ideas.
Public Safety Technology
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Author: Garry Tan
Everyone should feel safe in their homes and when walking on the streets. This is the basic security that a civilized society should provide to its citizens. Startups are already working in this area. For example, license plate cameras developed by Flock Safety (YCS 17) have helped solve 10% of reported crimes in the United States, and their goal is to increase this to 25% by next year. Meanwhile, Abel Police (YCS 24) reduces the time it takes police officers to fill out paperwork from hours to minutes, saving them up to 25% of their time per day for actual policing.
Public safety technology is and will continue to make a real difference. We especially want to hear from you if you are innovating in:
Advanced Computer Vision: Develop computer vision-based technologies that can identify suspicious activity or people in need of assistance from video streams while protecting individual privacy.
Emergency Response Technology: Technology that improves the speed and coordination of emergency response is critical. If you have an idea that can get help where it’s needed faster, we want to help you make it a reality.
Community Safety Tools: Develop tools that improve communities’ interactions with law enforcement, such as solutions that help neighbors look out for each other and stay informed about safety conditions.
Efficient Law Enforcement Technology: Technology that helps law enforcement work more efficiently and fairly, such as workload management systems or tools that increase operational precision.
If your startup is ready to join the wave of innovation in this space, we’d love to talk to you.
Made in the USA
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In the 19th century, Britain became the world’s richest country by becoming the “world’s factory.” The United States replicated this success in the 20th century. However, over the past few decades, the United States has gradually abandoned this role. The hollowing out of the manufacturing industry has not only exacerbated social and political divisions, but also put the United States in a geopolitically unstable position.
Bringing manufacturing back to the United States is one of the areas where there is strong bipartisan consensus. Elon Musk has shown us how feasible this goal is by building Tesla Gigafactories in Austin and Nevada. We believe that current technological advances provide more opportunities for a new generation of builders to emulate his success.
New robotic systems based on machine learning (ML) have made it possible to automate more of the production process, thereby reducing the labor cost gap of outsourcing manufacturing to other countries. In addition, companies like SpaceX and Tesla have trained a whole generation of engineers who have mastered how to create an American business that produces a physical product but operates like a startup.
We’ve already seen success with this model. For example, Astranis (W 16) builds telecommunications satellites in the heart of San Francisco, where warships were built for the U.S. Navy during World War II. Gecko Robotics (W 16), based in Pittsburgh, an old industrial center in the U.S., focuses on making robots for industrial inspection. Solugen (W 17) produces industrial chemicals at a large plant in Houston.
Stablecoin 2.0
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By Brad Flora and Harj Taggar
Earlier this year, we published a request for more stablecoin startups. Since then, the stablecoin space has only gotten better. For a long time, the main challenge for stablecoins has been regulation, and several attempts to pass stablecoin regulation in the United States have failed. But now, the outlook for stablecoin regulation in the United States is more optimistic, and we expect reasonable legislation to be introduced soon.
This year, stablecoin payment transactions have surged, now accounting for more than one-fifth of Mastercards payments. Nearly 30% of global remittances are completed through stablecoins, and traditional financial institutions (such as Visa) are also providing banks with platforms to issue their own stablecoins. In addition, Stripe recently acquired a stablecoin startup Bridge for $1 billion, which will undoubtedly attract more investors and capital into the field.
Therefore, now is one of the best times to launch a stablecoin startup. We are particularly interested in ideas from the following directions:
Services for businesses to help them hold and manage stablecoins more easily.
Provide developers with easy-to-use tools to quickly integrate stablecoin functionality.
If you are exploring innovations related to stablecoins, we would love to talk to you.
Large Language Models for Chip Design (LLMs for chip design)
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Author: Garry Tan
Every technological breakthrough in AI drives the demand for more powerful chips to support the training of larger models. In this technological race, no country wants to fall behind. The design and manufacture of chips is not only an economic issue, but also the key to survival in the post-AI era. OpenAIs O1 model shows us that large language models (LLMs) with reasoning capabilities can drive major breakthroughs in science and engineering. We are very interested in any team that uses LLMs to improve chip design.
We are particularly interested in teams that focus on designing ASICs (application-specific integrated circuits) and FPGAs (field-programmable gate arrays). Traditionally, designing customized digital systems requires a lot of development, design, and testing costs, so FPGA and ASIC research and development has always been a high-cost, high-threshold field. With the emergence of large language models, these costs are falling significantly, making more types of specialized computing possible.
Currently, most computers use the Von Neumann architecture, which handles programs and data through a single shared memory and operates through serial fetch and execution cycles. The advantage of this architecture is high flexibility and easy reprogramming of the system. However, for specific tasks (such as cryptocurrency mining, data compression or dedicated encryption tasks), by optimizing algorithms and hardware design, it is possible to achieve a 5 to 100 times increase in computing speed while reducing energy consumption by 10 to 100 times.
Below is a diagram provided by Taner Sadikoglu showing the difference in data flow between an optimized FPGA system and a traditional CPU.
Considering the orders of magnitude performance gains that FPGAs and ASICs can deliver, optimizing this process with LLMs could yield extremely valuable results and create huge business opportunities for startups.
Fintech 2.0
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The past two years have been challenging for Fintech startups. The collapse of Silicon Valley Bank led to regulators tightening restrictions on new startups and investors retreating from the space. However, we believe this is about to change and now is the best time to start a Fintech startup.
In the past, the hardest part of launching a financial startup was getting an agreement with a bank or other regulated partner. Now, with the emergence of service providers like Stripe and the popularity of new technologies like stablecoins, this process is becoming easier.
The rapid development of AI tools will inevitably drive changes in the financial industry. For small startups without the burden of traditional systems, this change brings structural advantages, enabling them to quickly build future global financial products.
We believe that now is the ideal time to create a new generation of fintech companies based on the existing infrastructure. We hope to see innovative ideas around insurance, investment banking, wealth management, international payments and more.
New space companies
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By Jared Friedman and Dalton Caldwell
The cost of accessing space is falling rapidly, having dropped more than 10-fold since SpaceX’s first launch in 2006. Today, a startup can build and launch a satellite with just a seed round of funding.
As access to space becomes as routine and low-cost as commercial aviation, shipping, or cargo, this will unlock many new business opportunities. Can you imagine how many kilograms of payload are launched into space today? How will this number grow in one year, five years, ten years?
While starting a space company may seem ambitious, it ’s not necessarily harder than starting a software company . YC has funded several space companies, including Astranis, Relativity Space, and Stoke, and their success rate may even exceed that of companies in other fields.
AI-aided engineering tools
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Author: Diana Hu
Engineering tools for the physical world have made little real progress in decades. The CAD/CAM software used by mechanical engineers, the EDA tools used by electrical engineers, and the CFD tools used by aerospace engineers—these tools still rely on complex numerical solvers and physics simulations. These tools are not only computationally expensive, but also require deep expertise, sometimes even a Ph.D., to use effectively.
We believe that a new generation of AI-driven tools will revolutionize this.
By incorporating the reasoning capabilities of mathematical and physical problem solving into new AI models, we can help engineers design and build physical systems such as aircraft, buildings, circuits, chips, and satellites faster and with higher quality.
We expect the founders to develop AI-assisted engineering tools to drive this change and become the driving force for the next generation of computer-aided engineering (CAE).
One million jobs 2.0
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We want to fund startups that can create a million jobs that require humans to do the work and do not rely on AI to replace them.
Historically, whenever there has been a major change in technology, the types of jobs people do have changed. For example, many people used to be farmers, but as mechanization became more common, the agricultural labor force has shrunk significantly. Similarly, occupations such as elevator operators and typists have gradually disappeared.
However, technological change often creates new occupations that are better equipped and deliver greater value to humanity. In this new AI-driven world, these occupations may include giving more people the tools to run their own local businesses or earn a living by providing services to others, either online or offline.
Many AI futurists are uncertain about what their careers will look like in the future, and we want to fund founders who can answer that question.
