Artificial English tutor that understands your situation and needs - writes email for your English speaking boss, prepares you for a job interview in your specific industry, etc.
I love how this is pretty off the cuff. Gives me a good idea of the actual, unscripted personalities of the group partners, and what they’re like in a group. Awesome guys!
Chapters (Powered by ChapterMe) - 00:00 - Intro: Differentiating Startup Ideas 00:48 - The Light Cone" Podcast 01:53 - Y Combinator's Recent Batch 03:34 - College Students and AI Startups 04:44 - AI Startup Success Factors 05:53 - Opportunities in Mundane AI Tasks 07:43 - Beware of "Tarpit Ideas" 08:30 - AI Copilot 09:36 - AI Integration into UIs 10:30 - Avoiding the "Checkbox Mentality" 11:54 - Focus on Genuine Use Cases 13:45 - Fine-Tuning Open-Source Models 15:20 - Data Privacy Concerns 16:31 - Purpose-Trained AI Models 18:36 - AI Models for Prototyping 19:45 - Surge in Startup Ideas 20:54 - The "GPT Wrapper" Term: Importance of UX 22:20 - Building a billion-dollar AI company: Focus on Specific Problems 24:16 - AI-Powered Voice Agents 25:50 - Advocacy for Open-Source AI 26:58 - Resurgence of AI Researcher-Founders 29:36 - Returning YC to Its Roots 30:20 - Periodic Dismissal of Emerging Tech 30:55 - Classic Hacker News Essay: The New Cycle of Tech Geeks 32:06 - Outro
The difference is: MySQL doesn’t have a consumer facing product. And in SaaS, the user interactions are much more complex. In Chat based software, it’s the same interaction. And there’s a consumer facing app already. 22:45 This means the barriers to entry are low, which means endless substitutes, which means you'll compete on price (race to the bottom)... low margins, low top line... this isn't rocket science.
That works both ways though. It means open source will likely win in the end since all it takes is one massive LLM to be trained so OAI and the like will lose their moat. I actually think access to chips will likely be the limiting factor, and I can see arguments for both OSS and closed source there.
00:00 - Intro: Differentiating Startup Ideas 00:48 - The Light Cone" Podcast 01:53 - Y Combinator's Recent Batch 03:34 - College Students and AI Startups 04:44 - AI Startup Success Factors 05:53 - Opportunities in Mundane AI Tasks 07:43 - Beware of "Tarpit Ideas" 08:30 - AI Copilot 09:36 - AI Integration into UIs 10:30 - Avoiding the "Checkbox Mentality" 11:54 - Focus on Genuine Use Cases 13:45 - Fine-Tuning Open-Source Models 15:20 - Data Privacy Concerns 16:31 - Purpose-Trained AI Models 18:36 - AI Models for Prototyping 19:45 - Surge in Startup Ideas 20:54 - The "GPT Wrapper" Term: Importance of UX 22:20 - Building a billion-dollar AI company: Focus on Specific Problems 24:16 - AI-Powered Voice Agents 25:50 - Advocacy for Open-Source AI 26:58 - Resurgence of AI Researcher-Founders 29:36 - Returning YC to Its Roots 30:20 - Periodic Dismissal of Emerging Tech 30:55 - Classic Hacker News Essay: The New Cycle of Tech Geeks 32:06 - Outro
Thank you for this podcast, you gave me the idea of taking 3 Google Cloud certifications: Cloud Architect, Data Engineer, Machine Learning Engineer to create one of the companies that you recommended to do. Your reviews are really helpful. Thank you 😃
love the modeling around "if a company isn't buying your co-pilot, just build their company with co-pilot and beat them" because if your co-pilot can't level up a company enough to be better than your potential client, then you probably aren't providing enough value.
2 Things I've advised our clients to consider with AI: > Focus on the picks and shovels: Enable AI rather than create it. > Double click on a niche: Don't just focus on an industry but a niche within a single industry. e.g. Not just antiques but antique books.
About the first, I think a lot of clients want all-in-one observability platforms that typically just get built by the biggest players (e.g. Azure), it seems like niche ideas may win in that field as well
Jeez, the subtitles kept showing Rapper, first I was like what ! Then I rationalized it saying as GPTs are language models spewing words they in a light heart calling it Rapper
10 หลายเดือนก่อน +25
Yo plz don't give up on this podcast. Looking forward to ep 100!
Honestly, I feel like the gold rush around AI and LLMs is creating this negative pressure on the rest of the ecosystem. I think it's pretty likely that we're going to see a huge consolidation in the LLM space in the coming years and there will be a few huge winners and lots of small losers. My hot take is that now is paradoxically the best time to found startups that *aren't* banking on AI and LLMs. Lots of people are going to waste lots of time trying to shoehorn LLMs into spaces they don't belong and fail, and it's a great time to get ahead. You were talking about AI tarpits, I think it's not that there are a few tarpits, but that AI is a giant tarpit with a few paradise-like islands. Build something great while others are swimming in the tar.
I agree completely, it seems like the pressure is making people ignore huge red flags, such as the fact that so many startups are based on the behaviour of openAIs models that can change on a daily basis.
This is an excellent conversation straight from the source of one of the best places tech is born. Thanks for starting this Y Combinator Team. I do so many tech startup interviews myself as a host for Grit Daily mag its refreshing to see what Y Combinator sees as important to discuss.
Most of the problems are like ages old. When tech meet use cases, they seem like strange to each other. So many mundane tasks are around us, and just a little bit calibration, these job would intrigue people's potential rather than make them age faster. Talk to the people in different industries, understand them, are so important.
Light cone is such a cool and appropriate name, and the explanation deserves a little expansion: Alpha centauri is 4 light years away, so any choice I make today will only affect alpha centauri 4 years from now, at the earliest, because nothing can travel faster than light. If you plot a spacetime graph of all the events throughout the universe that I could theoretically have an impact on, that graph will form a cone shape, which is why it's called a light cone. A very apt metaphor for starting a company that will shape the future!
A light cone in special relativity does does not refer to the spatial cone shape produced by a flashlight. Maybe im confused abt what he meant. It actually is related to the cone shape that all possible trajectories of light produce on a local spacetime diagram. For a given starting point it defines a boundary that no object can ever cross.
🎯 Key Takeaways for quick navigation: 19:30 🔍 *Startups see abundant opportunities in building AI applications.* 20:54 💡 *Generative AI ideas are popular but raise sustainability concerns.* 22:31 🎯 *Successful startups address specific user needs with tailored solutions.* 24:19 🚀 *Multimodal AI enhances software functionality, prompting innovation.* 25:18 🗣️ *AI voice agents automate tasks, but concerns arise over misuse.* 26:12 🌐 *Advocacy for open-source AI fosters equitable access and prevents monopolies.* 27:57 🚀 *Growing interest in AI entrepreneurship driven by successful technology transfer.* 30:01 🔄 *AI innovation attracts passionate technologists, echoing historical cycles.* 31:52 💪 *Perseverance and practical focus are vital in navigating AI entrepreneurship.*
The new gen ai stuff kind of yeah. But the ai that has been getting used for proper problems before this hype bubble, no. Example. Recommendation algos, which fall into the category of ai. Or optical character recognition which also falls under ai but has existed for over 20 years with plenty of problem solving use.
I’m a GPT-4 customer. I’m frustrated with the overconfidence in responses that end up being wrong. I’m also frustrated with its laziness and not knowing where the laziness starts and ends. I asked it to give me a list of all the countries in the world and it was adamant that I just go to a Wikipedia page.
Note for myself: Popular ideas for AI startups that are not working(tarpit ideas) AI copilot: Build a copilot for someone's product or service. Finetuning open-source models. Ideas working: LLM security.
These guys literally became millionaires in the era where explicitly unprofitable businesses were given tens of millions in funding… what do you expect lol
3:55 - I don't believe in coincidences. I decided to finally go back to college & earn a CS degree I started years prior. And about 3 months before graduating, an old friend asked me to partner with him on an AI startup. So I'm grateful to say not only am I getting in on this once-in-a-lifetime opportunity, but doing it with a fresh current Computer Science education. Granted the timing worked out for me, but I do believe there is more benefit to earning that degree while still jumping into this world. Great video, thanks!!
First, great show. I appreciate getting into the nuts-n-bolts, but also appreciate higher level talk shows like this. Thank you. Secondly, what is the name of the Government contracting AI company/tool that you mentioned? I almost fell off my seat when I heard someone was doing this. I started this very same thing, however, it's a 50/50 split of code and AI, as I've found at least 50% of a Sources Sought response or Market Survey response is a regurgitation of what can be found through code. In any case, if I can pay for an already operational SaaS for this, I would gladly do that in place on finishing what I've been working on.
Thanks for the insightful conversation! I just need more clarification on the ideas that seems to be good but they can be taken away by gpt-5. I have a lot of ideas for gen-ai projects but the thing is that are they good enough to stand for the next era. honestly i think it is a marathon of innovation, when gpt-5 unleashes, we jump to new products now the question is do we abandon those we had?
It is very interesting how AI is changing the way we find information and work around the world so exponentially. Investing in large companies dedicated to AI is a smart move. Many companies, are and will continue to migrate to this new technology, it saves money if a robot can do a job instead of a person.
for others closer to my age (mid 40s and up), I have a course on skool called prompt-engineering , I taught kindergarten 9 years then went to computer science/ data science school/ bootcamps with the kids, now 8 years in tech, working as an ai integrated specialist
On skool, I have a course called prompt-engineering , I do live zoom on Saturdays if people have questions. Not free but free stuff, you can find anywhere online
I love the episode, it's really insightful and would love to have more. But I would like it if most of the acronyms used could be outlined to help those unfamiliar with them add them to their vocabulary. Thank you
Such an underwhelming explanation of the lightcone. It’s the space-time region that any physical entity can be causally connected to! Such a cool podcast title!
Interesting, that YC are saying replacing mundane data jockey work is perfect for replacement by LLM, when it seems that an ML orchestration engine with an LLM connector, makes more sense?
If models become local (stored and processed on prem for mobile and desktop) Then applications serve as a literal UI layer. Apps become more lightweight going forward?
AI is changing the way we access information and the way we work. Even just investing in the major public players is a great way to get exposure to AI. It simply makes sense economically if you can have a robot do what you need to pay a human to do.
Love this podcast. One quick suggestion, the light cone is not exactly the definition you mentioned in the beginning. It's related to time and light speed so that have the cone shape. Just a suggestion.
On the issue of inefficient prompting by the average user as described @9:20, I have an idea for an Ai co-pilot that works alongside the standard chat interface with ChatGPT, but operates on a meta level to discern what the user is attempting to communicate to ChatGPT and coaches them on more accurate prompts to get better results. I don’t know if I would pay for that, but I would definitely use it. To bridge that purchase gap, it could be added into a Swiss Army knife Ai-copilot with different al-a-cart features that each person could customize for their workflow. It would inevitably be overshadowed by AGI in the long run, but until that gets here, there is definitely a market for that in the small-business entrepreneurial sector.
Takeaways generated by Zenfetch: 1. Many assume YC favors AI startups but the partners say they fund smart founders irrespective of industry. 2. College students and young founders are well positioned to work in AI due to the newness of the field and lack of experience requirements. 3. Automating repetitive human tasks using AI, such as searching and form filling, is an area seeing applications being built.
Thanks, Y Combinator, for the knowledge shared. I'm exploring a niche within the LLM-based AI tool space, similar to what Agent GPT offers, but more focused. Given that broader AI tools like the upcoming GPT-5 may not cater specifically to every unique problem or audience, how viable do you think a specialized, niche AI solution is? Can targeting a specific audience with tailored solutions still be a sustainable business model despite the broader capabilities of general AI platforms?
Can we talk about an app for consumers to buy cars inwhich ai provides certain car searches and provides certain data on cars and educated the buyer to be able to buy the car they desire? Can I work with someone to make this possible?
I'm building an AI startup, and I'm from Africa, currently studying in India. Although 'm facing lots of impediments, and from an impoverished origin, I hope eventually my AI gets funded by YCombinator.
Exciting start! The Lightcone Podcast's debut episode, featuring insights from YC Group Partners working with top AI startup founders, promises a treasure trove of valuable lessons.
Well from what I understand that AI as it stands is very difficult to implement, but even more difficult to get people to use, which is closer to my experience. The solution to this is to design an AI that the user doesn't necessarily interact with, but functions in the background (usually as an auto-complete). I think that's probably the direction to go in first, and then once we figure how to use AI as a really sophicated auto-complete, then we can properly move on to auto-gen bots that can just use the tools without supervision. Finally once it understands how to just use the tools as good as a human, then we can go into full automation, where we just give it a task, and it will complete it, as well as a human can.
Just curious, it's interesting how every one of you mentioned LLMs, but no one talked about CNNs (Convolutional Neural Networks). Is it because there are so few computer vision-related startups applying or generally building in this area? Great first episode, by the way. Always love your content, can't wait for future episodes - it's going to be epic!
What are you building with AI right now?
Ecommerce shopping agent & AI ethics research.
Props AI - A cost monitoring tool for Open AI spend
Artificial English tutor that understands your situation and needs - writes email for your English speaking boss, prepares you for a job interview in your specific industry, etc.
How do I get funding? I want to bring AI powered Vtubers to the masses. I am also working on custom chatbots
Mitra - build AI teams that do anything
I love how this is pretty off the cuff. Gives me a good idea of the actual, unscripted personalities of the group partners, and what they’re like in a group. Awesome guys!
They feel more human haha!
It's not everday that YC launches a new podcast! Love the name and the content, keep em coming!
Chapters (Powered by ChapterMe) -
00:00 - Intro: Differentiating Startup Ideas
00:48 - The Light Cone" Podcast
01:53 - Y Combinator's Recent Batch
03:34 - College Students and AI Startups
04:44 - AI Startup Success Factors
05:53 - Opportunities in Mundane AI Tasks
07:43 - Beware of "Tarpit Ideas"
08:30 - AI Copilot
09:36 - AI Integration into UIs
10:30 - Avoiding the "Checkbox Mentality"
11:54 - Focus on Genuine Use Cases
13:45 - Fine-Tuning Open-Source Models
15:20 - Data Privacy Concerns
16:31 - Purpose-Trained AI Models
18:36 - AI Models for Prototyping
19:45 - Surge in Startup Ideas
20:54 - The "GPT Wrapper" Term: Importance of UX
22:20 - Building a billion-dollar AI company: Focus on Specific Problems
24:16 - AI-Powered Voice Agents
25:50 - Advocacy for Open-Source AI
26:58 - Resurgence of AI Researcher-Founders
29:36 - Returning YC to Its Roots
30:20 - Periodic Dismissal of Emerging Tech
30:55 - Classic Hacker News Essay: The New Cycle of Tech Geeks
32:06 - Outro
Very good summary
@@rembautimes8808 thank you 😊
Clever ;)
@@nathanbrannan5228 Thanks 🙃
now i can skip to whatever complete trash their taking about
30 minutes is about the perfect length for a podcast episode 👌
4 you. i perfer 3 hours.
A lot of info
Love the energy and maturity around the topic! Waiting for Ep2!
"Mundane tasks and boring work"! Love this!
Thanks for the inspiring conversation
The difference is: MySQL doesn’t have a consumer facing product.
And in SaaS, the user interactions are much more complex.
In Chat based software, it’s the same interaction. And there’s a consumer facing app already. 22:45
This means the barriers to entry are low, which means endless substitutes, which means you'll compete on price (race to the bottom)... low margins, low top line... this isn't rocket science.
Agreed
That works both ways though. It means open source will likely win in the end since all it takes is one massive LLM to be trained so OAI and the like will lose their moat.
I actually think access to chips will likely be the limiting factor, and I can see arguments for both OSS and closed source there.
I feel like this is the start of something special.
same, in no other circumstance you have this level of intelligence converge on a podcast for any reason.
00:00 - Intro: Differentiating Startup Ideas
00:48 - The Light Cone" Podcast
01:53 - Y Combinator's Recent Batch
03:34 - College Students and AI Startups
04:44 - AI Startup Success Factors
05:53 - Opportunities in Mundane AI Tasks
07:43 - Beware of "Tarpit Ideas"
08:30 - AI Copilot
09:36 - AI Integration into UIs
10:30 - Avoiding the "Checkbox Mentality"
11:54 - Focus on Genuine Use Cases
13:45 - Fine-Tuning Open-Source Models
15:20 - Data Privacy Concerns
16:31 - Purpose-Trained AI Models
18:36 - AI Models for Prototyping
19:45 - Surge in Startup Ideas
20:54 - The "GPT Wrapper" Term: Importance of UX
22:20 - Building a billion-dollar AI company: Focus on Specific Problems
24:16 - AI-Powered Voice Agents
25:50 - Advocacy for Open-Source AI
26:58 - Resurgence of AI Researcher-Founders
29:36 - Returning YC to Its Roots
30:20 - Periodic Dismissal of Emerging Tech
30:55 - Classic Hacker News Essay: The New Cycle of Tech Geeks
32:06 - Outro
Thanks for doing this.
How would you do it for my vids?
Thank you for this podcast, you gave me the idea of taking 3 Google Cloud certifications: Cloud Architect, Data Engineer, Machine Learning Engineer to create one of the companies that you recommended to do. Your reviews are really helpful. Thank you 😃
Another day, another YC Classic.
love the modeling around "if a company isn't buying your co-pilot, just build their company with co-pilot and beat them" because if your co-pilot can't level up a company enough to be better than your potential client, then you probably aren't providing enough value.
Excited to see where this podcast goes! lots of things to learn from you guys! thanks!
Working in an AI startup, I can vouch for these observations. They were on point, to which we are working on right now!
The analogy of LLM as FPGA of idea prototyping is quite apt !
2 Things I've advised our clients to consider with AI:
> Focus on the picks and shovels: Enable AI rather than create it.
> Double click on a niche: Don't just focus on an industry but a niche within a single industry. e.g. Not just antiques but antique books.
About the first, I think a lot of clients want all-in-one observability platforms that typically just get built by the biggest players (e.g. Azure), it seems like niche ideas may win in that field as well
Key takeaway: "SaaS is just a DataBase Wrapper", golden phrase right there.
Jeez, the subtitles kept showing Rapper, first I was like what ! Then I rationalized it saying as GPTs are language models spewing words they in a light heart calling it Rapper
Yo plz don't give up on this podcast. Looking forward to ep 100!
yes sir
Honestly, I feel like the gold rush around AI and LLMs is creating this negative pressure on the rest of the ecosystem. I think it's pretty likely that we're going to see a huge consolidation in the LLM space in the coming years and there will be a few huge winners and lots of small losers. My hot take is that now is paradoxically the best time to found startups that *aren't* banking on AI and LLMs. Lots of people are going to waste lots of time trying to shoehorn LLMs into spaces they don't belong and fail, and it's a great time to get ahead. You were talking about AI tarpits, I think it's not that there are a few tarpits, but that AI is a giant tarpit with a few paradise-like islands. Build something great while others are swimming in the tar.
Every startup can be a tar pit if you can’t raise funding 😅
I agree completely, it seems like the pressure is making people ignore huge red flags, such as the fact that so many startups are based on the behaviour of openAIs models that can change on a daily basis.
This is an excellent conversation straight from the source of one of the best places tech is born.
Thanks for starting this Y Combinator Team.
I do so many tech startup interviews myself as a host for Grit Daily mag its refreshing to see what Y Combinator sees as important to discuss.
Most of the problems are like ages old. When tech meet use cases, they seem like strange to each other. So many mundane tasks are around us, and just a little bit calibration, these job would intrigue people's potential rather than make them age faster. Talk to the people in different industries, understand them, are so important.
Light cone is such a cool and appropriate name, and the explanation deserves a little expansion: Alpha centauri is 4 light years away, so any choice I make today will only affect alpha centauri 4 years from now, at the earliest, because nothing can travel faster than light. If you plot a spacetime graph of all the events throughout the universe that I could theoretically have an impact on, that graph will form a cone shape, which is why it's called a light cone. A very apt metaphor for starting a company that will shape the future!
A light cone in special relativity does does not refer to the spatial cone shape produced by a flashlight. Maybe im confused abt what he meant. It actually is related to the cone shape that all possible trajectories of light produce on a local spacetime diagram. For a given starting point it defines a boundary that no object can ever cross.
5:48 LLMs are NOT great at all at automated consistent data conversion. Why would you state this do confidently?
Absolutely amazing talk very bright panel
Best video I watched in a while. Thank you! It's good to have validation that what we are doing is correct.
🎯 Key Takeaways for quick navigation:
19:30 🔍 *Startups see abundant opportunities in building AI applications.*
20:54 💡 *Generative AI ideas are popular but raise sustainability concerns.*
22:31 🎯 *Successful startups address specific user needs with tailored solutions.*
24:19 🚀 *Multimodal AI enhances software functionality, prompting innovation.*
25:18 🗣️ *AI voice agents automate tasks, but concerns arise over misuse.*
26:12 🌐 *Advocacy for open-source AI fosters equitable access and prevents monopolies.*
27:57 🚀 *Growing interest in AI entrepreneurship driven by successful technology transfer.*
30:01 🔄 *AI innovation attracts passionate technologists, echoing historical cycles.*
31:52 💪 *Perseverance and practical focus are vital in navigating AI entrepreneurship.*
So is AI a solution in search of a problem?
The new gen ai stuff kind of yeah. But the ai that has been getting used for proper problems before this hype bubble, no. Example. Recommendation algos, which fall into the category of ai. Or optical character recognition which also falls under ai but has existed for over 20 years with plenty of problem solving use.
Not at all. It has already revolutionized our law firm and there are real world consequences for our clients.
This is very insightful! Keep up the good work, team YC!
Thank you. Interesting times. Look forward to more episodes!
This is a gem. every minute is packed with good ideas.
I’m a GPT-4 customer. I’m frustrated with the overconfidence in responses that end up being wrong. I’m also frustrated with its laziness and not knowing where the laziness starts and ends. I asked it to give me a list of all the countries in the world and it was adamant that I just go to a Wikipedia page.
Completely agree. Same experience.
Building a startup should start from problems.
Building an AI startup should start from problems, too, not AI.
Data privacy is the main driver for customers looking into hosting their own LLMs specially in regulated markets in the EU
A half hour is very brief. I'd love to hear more about how you see the world.
Don’t worry we post a new episode of Lightcone every two weeks
very insightful, keep it coming! thanks for sharing
yes
Note for myself:
Popular ideas for AI startups that are not working(tarpit ideas)
AI copilot: Build a copilot for someone's product or service.
Finetuning open-source models.
Ideas working: LLM security.
I think you are right it's crowded place there is more ai startups than demand
Why does an AI copilot ain't work?
@@ephreamjudegeorge8063 there are many industry giants already like ibm unless you want to get f up.Better do something on other products
My favourite moment 10:30 “Companies being asked What’s our AI strategy” and selling them something to tick the box
So the truth is you all funded AI without having any idea what the use case is and now everyone is stuck in a bubble.
That's really accurate
These guys literally became millionaires in the era where explicitly unprofitable businesses were given tens of millions in funding… what do you expect lol
It sounds like a bunch of marketers knowing nothing about tech and especially about llms
@@abesari29so true.
If execute your story nice enough, you're a guru. If you fail, you're a con artist 😀
4:18 the same applies to gen x and any age group…the LLM technology is new for almost everyone
Curious how much should LLM API costs be for B2B SaaS built using LLMs - 10%?
Noting a namespace collision: Lightcone Infrastucture (often just called Lightcone) is the parent organization of LessWrong.
Many such cases
Its not a legal problem so I say go ahead.
Really like the format and the wisdom here!
Thank you for this podcast.
What a great ending, man!
as well as the whole podcast
Good content - Go YC! Great to see Diana there too!
Great episode, looking forward to more!👌🏿
3:55 - I don't believe in coincidences. I decided to finally go back to college & earn a CS degree I started years prior. And about 3 months before graduating, an old friend asked me to partner with him on an AI startup. So I'm grateful to say not only am I getting in on this once-in-a-lifetime opportunity, but doing it with a fresh current Computer Science education. Granted the timing worked out for me, but I do believe there is more benefit to earning that degree while still jumping into this world. Great video, thanks!!
Love the genesis of the Lightcone name, Jared :) Looking forward to more of these chats.
Thanks guys. This video inspired me to implement LLM to a feature I’m currently building for my startup.
How come i didn’t think about it that way 😊
Love love love love this channel
First, great show. I appreciate getting into the nuts-n-bolts, but also appreciate higher level talk shows like this. Thank you. Secondly, what is the name of the Government contracting AI company/tool that you mentioned? I almost fell off my seat when I heard someone was doing this. I started this very same thing, however, it's a 50/50 split of code and AI, as I've found at least 50% of a Sources Sought response or Market Survey response is a regurgitation of what can be found through code. In any case, if I can pay for an already operational SaaS for this, I would gladly do that in place on finishing what I've been working on.
what are some good AI stuff examples done in drastically cheaper way but the conventional thought was it mi8 cost us so much?
Thanks for the insightful conversation! I just need more clarification on the ideas that seems to be good but they can be taken away by gpt-5. I have a lot of ideas for gen-ai projects but the thing is that are they good enough to stand for the next era. honestly i think it is a marathon of innovation, when gpt-5 unleashes, we jump to new products now the question is do we abandon those we had?
They should link their linkedIn/social media on the descriptions so we could follow
It is very interesting how AI is changing the way we find information and work around the world so exponentially. Investing in large companies dedicated to AI is a smart move. Many companies, are and will continue to migrate to this new technology, it saves money if a robot can do a job instead of a person.
This is the best thing happening on the internet right now!🔥
What's the third company logo in the thumbnail that's not Anthropic or OpenAI?
The third company logo in the thumbnail that is not Anthropic or OpenAI is Y Combinator (YC).
Answered by Talkbud
for others closer to my age (mid 40s and up), I have a course on skool called prompt-engineering , I taught kindergarten 9 years then went to computer science/ data science school/ bootcamps with the kids, now 8 years in tech, working as an ai integrated specialist
On skool, I have a course called prompt-engineering , I do live zoom on Saturdays if people have questions. Not free but free stuff, you can find anywhere online
Best 32 minutes i attended in a while.
TIMESTAMPS -- Please, it's 2024, and we want to be able to skip around based on topics!
Whats the point of all the A.I. projects if AGI is around the corner?
I love the episode, it's really insightful and would love to have more.
But I would like it if most of the acronyms used could be outlined to help those unfamiliar with them add them to their vocabulary. Thank you
Such an underwhelming explanation of the lightcone. It’s the space-time region that any physical entity can be causally connected to! Such a cool podcast title!
What does it mean "we just fund the smart founder"?
How do you understand which one is the smart founder?
Quick question here: what was the controversy behind the SQL / database wrappers & the negative response to it? what was the point?
Oh it never happened. That’s why the GPT wrapper idea is absurd.
@@ycombinator gotcha, thank you:) and double thanks to this amazing content - answered so many questions - looking forward to the next episode
Interesting, that YC are saying replacing mundane data jockey work is perfect for replacement by LLM, when it seems that an ML orchestration engine with an LLM connector, makes more sense?
For a lot of use cases it doesn’t make sense to use LLMs (it’s overkill). Using just ML is even more boring and probably is enuff for most problems
@@HenleyWingI think every big corporations now use ai so where will they get market
If models become local (stored and processed on prem for mobile and desktop)
Then applications serve as a literal UI layer.
Apps become more lightweight going forward?
Great startup idea lying on the ground: make it easy for viewers to fix youtube transcript (so it can pass the touring test)
lol exactly what I thought 😂
Turing Test.
AI is changing the way we access information and the way we work. Even just investing in the major public players is a great way to get exposure to AI. It simply makes sense economically if you can have a robot do what you need to pay a human to do.
Who's gonna buy all the junk that robots are making, when the average person can no longer afford to pay for their housing and food?
This is incredible. Everyone of you looks and sounds great too.
Thank you for this conversation!
I am a geek and love innovations and cutting edge in AI.
Can you code?
thanks for this Gary 👍
So if you work full time and your startup idea funded. Does that funding go to your salary so you can work on it full time?
Your decision, not VC decision bro
As a german startup founder I directly recognized this intro jingle 😅 - shout out to all OMR education listener ✌❤
I love the FPGA vs SOC analogy.
I love Will Ferrell being an intricate part of the YC team.
How can someone pitch Y C for an AI startup?
I love this conversation! It's about time
Love this podcast. One quick suggestion, the light cone is not exactly the definition you mentioned in the beginning. It's related to time and light speed so that have the cone shape. Just a suggestion.
On the issue of inefficient prompting by the average user as described @9:20, I have an idea for an Ai co-pilot that works alongside the standard chat interface with ChatGPT, but operates on a meta level to discern what the user is attempting to communicate to ChatGPT and coaches them on more accurate prompts to get better results.
I don’t know if I would pay for that, but I would definitely use it. To bridge that purchase gap, it could be added into a Swiss Army knife Ai-copilot with different al-a-cart features that each person could customize for their workflow. It would inevitably be overshadowed by AGI in the long run, but until that gets here, there is definitely a market for that in the small-business entrepreneurial sector.
Takeaways generated by Zenfetch:
1. Many assume YC favors AI startups but the partners say they fund smart founders irrespective of industry.
2. College students and young founders are well positioned to work in AI due to the newness of the field and lack of experience requirements.
3. Automating repetitive human tasks using AI, such as searching and form filling, is an area seeing applications being built.
sup gabe
Fantastic. Best podcast I've listened to in a long time. How do I get in. I want in.
Very insightful!!!
Thanks, Y Combinator, for the knowledge shared. I'm exploring a niche within the LLM-based AI tool space, similar to what Agent GPT offers, but more focused. Given that broader AI tools like the upcoming GPT-5 may not cater specifically to every unique problem or audience, how viable do you think a specialized, niche AI solution is? Can targeting a specific audience with tailored solutions still be a sustainable business model despite the broader capabilities of general AI platforms?
No for long term. The general use AI is growing and developing rapiy and becoming close to the solution people need
PromptArmour is actually changing the game! Can't wait to see what they do next!
love this! keep it up ,please!!
Thank you very much guys for that amazing episode , helpful insights ❤
Can we talk about an app for consumers to buy cars inwhich ai provides certain car searches and provides certain data on cars and educated the buyer to be able to buy the car they desire? Can I work with someone to make this possible?
I'm building an AI startup, and I'm from Africa, currently studying in India.
Although 'm facing lots of impediments, and from an impoverished origin, I hope eventually my AI gets funded by YCombinator.
I tried applying for an idea with fine tuned LLMs replacing psycho-therapist.Didn't get selected even for interviews😭.
Where do you really see people doing the same research tasks all the time and summarizing their work? 5:46
I love your videos, continue pls
Exciting start! The Lightcone Podcast's debut episode, featuring insights from YC Group Partners working with top AI startup founders, promises a treasure trove of valuable lessons.
Well from what I understand that AI as it stands is very difficult to implement, but even more difficult to get people to use, which is closer to my experience.
The solution to this is to design an AI that the user doesn't necessarily interact with, but functions in the background (usually as an auto-complete).
I think that's probably the direction to go in first, and then once we figure how to use AI as a really sophicated auto-complete, then we can properly move on to auto-gen bots that can just use the tools without supervision.
Finally once it understands how to just use the tools as good as a human, then we can go into full automation, where we just give it a task, and it will complete it, as well as a human can.
Just curious, it's interesting how every one of you mentioned LLMs, but no one talked about CNNs (Convolutional Neural Networks). Is it because there are so few computer vision-related startups applying or generally building in this area?
Great first episode, by the way. Always love your content, can't wait for future episodes - it's going to be epic!
There are just fewer focused there but they do exist Eg Standard AI or Flock Safety
@@ycombinator Thanks for the clarification and quick response.
What is the paper from 2017 that she mentioned called? About ai translating from other theb english
“Attention is all you need”
@@ycombinator thxx 🚀🙏
Still percolating on "GPT Wrappers" and subsequent discussion.