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Big Tech and Generative AI
Big Tech and Generative AI
What the incumbents are up to with Generative AI
·tanay.substack.com·
Big Tech and Generative AI
The 4 Startup States During a Recession by @ttunguz
The 4 Startup States During a Recession by @ttunguz
As the fiscal quarters of many startups draw to a close, board members and management teams are having one of four conversations: The World is Your Oyster, Time to Strategize, Chewing Gravel, or Go Big/Go Profitable. Here’s how these scenarios fall onto a 2x2 matrix. The x-axis is the Zero Cash Date: when the startup runs out of money. The y-axis is sales efficiency: a proxy for product-market fit (PMF). Typically, most startups selling into the small-and-medium business segment would like to be in 14-18 months’ payback.
·tomtunguz.com·
The 4 Startup States During a Recession by @ttunguz
The Four Horsemen of the Tech Recession
The Four Horsemen of the Tech Recession
Tech is increasingly divorced from the real economy thanks to the COVID hangover and Apple’s App Tracking Transparency
·stratechery.com·
The Four Horsemen of the Tech Recession
APIs vs Composability In Web3 - by Peter Schroeder
APIs vs Composability In Web3 - by Peter Schroeder
So while the dream is composability through open-source, the reality seems to be interoperability through APIs
In my opinion, this is how the ecosystem comes together. Companies/people with motivation to build/connect to better unlock financial accessibility/compatibility
·apifirst.tech·
APIs vs Composability In Web3 - by Peter Schroeder
Only Intrinsic Motivation Lasts
Only Intrinsic Motivation Lasts
Why I quit a $500K job at Amazon to work for myself
The other comes from within. This is what drives me to do things when there isn’t a carrot or a stick. Hobbies are one activity driven by this. But what I was looking for was something that I could do for a living that was also driven by this type of motivation: the intrinsic kind.
·dvassallo.medium.com·
Only Intrinsic Motivation Lasts
Composable Models
Composable Models
In the last ML cycle, a specific strategy often beat out all others (at least in competitions) — ensemble models. This algorithm combines several weaker, simpler models to create a stronger, more robust model. As a result, nearly every Kaggle competition was won by an ensemble model — often composed of tens
·matt-rickard.ghost.io·
Composable Models
Disabled and out of work for years, but need some side income, what can I do? | Hacker News
Disabled and out of work for years, but need some side income, what can I do? | Hacker News
Regarding the $1,200 per month limit, I'm not sure what the rules are, but perhaps you could set up a corporation that takes on the freelancing jobs and then pays you a salary of $1,200 a month? That way you wouldn't have to turn down a job for paying too much.Maybe have the corp owned by a trust rather than you personally?I wouldn't want you to get in trouble and lose the disability, though, so talk to somebody who actually knows what they're talking about before doing any of this stuff.
·news.ycombinator.com·
Disabled and out of work for years, but need some side income, what can I do? | Hacker News
If It Doesn’t Ship, It Doesn’t Exist
If It Doesn’t Ship, It Doesn’t Exist
If it doesn’t ship, it doesn’t exist — Elad Gil (@eladgil) January 25, 2023 The top four companies with the most papers at NeurIPS, one of the leading AI/ML research conferences, are Google, Microsoft, Meta, and Deepmind (Google). The 2017 paper, Attention Is All You Need, which introduced
·matt-rickard.ghost.io·
If It Doesn’t Ship, It Doesn’t Exist
Optimal Stopping Theory
Optimal Stopping Theory
A company is looking to hire a worker out of n applicants, and the company knows that one of the applicants is the best. The company interviews the applicants individually, and after each interview, it must decide whether to hire the applicant or keep looking. If the company decides to
·matt-rickard.ghost.io·
Optimal Stopping Theory
The Frontend Bundling Cycle
The Frontend Bundling Cycle
In NextJS v13, the framework's compiler got 17x faster. Why? An extensible Rust-based platform for JavaScript compilation and bundling called swc. The compiler went v1 in 2019, and Vercel hired the lead developer in 2021. For a minute, Svelte/SvelteKit was emerging as a viable alternative to NextJS/Vercel. Now,
In NextJS v13, the framework's compiler got 17x faster. Why? An extensible Rust-based platform for JavaScript compilation and bundling called swc. The compiler went v1 in 2019, and Vercel hired the lead developer in 2021.
·matt-rickard.ghost.io·
The Frontend Bundling Cycle
Internal Tech Emails on Twitter
Internal Tech Emails on Twitter
Mark Zuckerberg: "VR / AR strategy"June 22, 2015 pic.twitter.com/Zp8B59kAAr— Internal Tech Emails (@TechEmails) January 29, 2023
·twitter.com·
Internal Tech Emails on Twitter
Updating The Hype Cycle
Updating The Hype Cycle
Reflecting on The AI Moment
For those of you who find yourselves feeling skeptical of this kind of "heat seeking," you should ask yourself what kind of investor are you? What kind of founder are you? Are you more focused on building long-term business value? Or are you focused on getting as wealthy as possible, as quickly as possible? Because those are not necessarily the same games. And whether its building long-term business value, or getting rich, it's certainly possible (even most likely) that you'll lose one of those games. But if you don't know what game you're playing? Well, then you're sure to lose.
·open.substack.com·
Updating The Hype Cycle
Becoming an emotionally fit founder | Calm Company Fund
Becoming an emotionally fit founder | Calm Company Fund
Being a founder is hard and to navigate the numerous roles and tasks that are needed of you, being resilient and able to deal with discomfort is key.
·calmfund.com·
Becoming an emotionally fit founder | Calm Company Fund
The Wizard of Oz Approach | Y Combinator
The Wizard of Oz Approach | Y Combinator
Dear YC, The product I’m building combines a variety of technologies like Hadoop and NLP, which I haven’t really worked with before. After an initial research phase where I learn and experiment, this technology would then have to be commercialized and added into my existing product. Any suggestions on staying on track, time, and budget? How should I keep the project focused? Sincerely, Aspiring Fast Learner -------------------------------------------------------------------------------- D
In some cases this isn’t possible. If it’s not, then ask yourself what is the minimum work you need to do to get to a product you can test with customers. For example, maybe you can make the algorithms work well for a narrow set of users, rather than solving the general case.
Once you know the minimum work, try to break it down into discrete steps, as many as possible. Your estimate of the time for the project will be more accurate if you evaluate each step and then add them up, rather than trying to estimate the whole thing at once. Having discrete steps with time estimates allows you to have checkpoints throughout the project so you can see if you are falling behind expectations. Tracking measurable progress frequently is the best way to stay on budget.
The latter is usually the most eye opening for founders when they finally ask themselves this honestly. Most of the time, the features asked by customers are not ones that they’d leave over if not built immediately. They’re nice to have, not need to have. When resources like time and energy are limited in a startup, knowing what not to do becomes invaluable.
Sometimes the answer is clear and it’s obvious that you must fix a critical bug over everything else. Boom, easy win. Sometimes it’s not as clear and your gut tells you that the feature no one asked for but is in your vision is the idea that will make the most impact on growth. That is where you, the founder, earn your equity. Time to make that tough decision! It may or may not work out, but at least you’re not making the decision arbitrarily. If it doesn’t work out, learn from the mistake, resort and move forward quickly.
·ycombinator.com·
The Wizard of Oz Approach | Y Combinator
The Art of Shipping Early and Often : YC Startup Library | Y Combinator
The Art of Shipping Early and Often : YC Startup Library | Y Combinator
When you’re going through Y Combinator, one piece of advice you receive is to “ship early” — to launch well before you think you’re ready. Here's how to make it a habit.
“Several distinct problems manifest themselves as delays in launching: working too slowly; not truly understanding the problem; fear of having to deal with users; fear of being judged; working on too many different things; excessive perfectionism. Fortunately you can combat all of them by the simple expedient of forcing yourself to launch something fairly quickly.” —-Paul Graham, The 18 Mistakes that Kill Startups
Our MVP gestation time kept shrinking, from three months, to one week, to one day, down to a few hours. In the end it was our most minimal release, a single page that submitted a file and an email address to our inbox, that got us the most traction.
Sometimes our features were so ridiculously basic that as soon as we released them, everyone complained about the lack of functionality. However, this was great: We’d wasted zero effort, and quickly knew that customers wanted that feature.
The main downside to this approach is that your product will feel less mature and polished than it could. But the feedback, data, and learning you get from releasing v0 features far outweighs the minor early reputation damage you may incur.
·ycombinator.com·
The Art of Shipping Early and Often : YC Startup Library | Y Combinator
When AI Favors the Incumbents by @ttunguz
When AI Favors the Incumbents by @ttunguz
In his most recent earnings conference call, Microsoft’s Satya Nadella said “Every product of Microsoft will have some of the same AI capabilities to completely transform the product.” Today, Microsoft Teams launched AI features in Teams for a fee. Teams will summarize meetings, create chapters in those meetings, extract tasks, translate in real time, & develop templates for future meetings. Incumbents have lept onto advances in generative machine learning more aggressively than any trend in recent technology history.
·tomtunguz.com·
When AI Favors the Incumbents by @ttunguz