John Valentine

@bhalligan I remember the electricity walking into those early @MassChallenge events at 1 Marina Park Drive with the 128 resident startups. Never knew who you'd run into. And the early @TechstarsBoston finales...so good.

@JohnnyStartup My memory was very crowded web meetups that Dharmesh and I would go to. This was the beginning of web2.0 and there was a ton of enthusiasm. A lot of people thought of HubSpot back then as Web2.0 marketing. We'd be around the YC stuff too, more Dharmesh than me, though.

I’m starting to worry about Massachusetts 1. Biotech is way off from a few years ago 2. Only 1 of the top 50 ai companies are in MA 3. The Fed research funding cuts hitting MIT, Harvard, Whoi are brutal. 4. The millionaires tax is working in the short run, but I know a lot of wealthy folks preparing for a FL move. 5. A glut of empty condos 6. It’s not “cool” for young folks 7. It’s expensive as sh-t. I honestly don’t think the MA/Boston govt can do that much about it as they are kind of macro issues. I give them big credit for working on building more housing and fixing the T, which will help. I’m trying to help w HubSpot, partnering w WHOI, teaching at MIT. I’d like to help more. Specifically I’d like to encourage and help more ai and climate companies in the state. I think ai and climate should be our dual growth engines.

Check out my latest article: Sam is Pot-Committed linkedin.com/pulse/sam-pot-… via @LinkedIn

F1 is the perfect Formula One movie because it’s just nonstop Hall of Fame level product placement. 6 Apple products onscreen before the title card, Brad Pitt refuses to accept a Rolex because he loves his IWC, someone even uses a Ninja blender!

@ejkalafarski And gave them plenty of time and justification to pivot if things went completely awry...

Chalking it up to "one bad night" treats it like a normal debate, which it wasn't. The early June debate was a big bet by the Biden campaign to change the narrative with another SOTU performance, but the big bet simply didn't pay off.

Despite me rolling over my 401k away from @Fidelity, their customer service in helping me make the transaction was respectful and thoughtful. Gives me a really positive view of their org. A great example of a financial services firm playing the long game. Well done.

@Sportrepreneur4 The Kareem of that set tho...

One of the coolest basketball cards in existence.

@hamdiulukaya @AnchorBrewing This man is a true business genius.

I am honored to work with the people of San Francisco to bring @AnchorBrewing, this dream, back to life.

Microsoft CTO @Kevin_Scott on what you should be building in the age of AI: Anything that used to be impossible, and is now merely hard.

One hard problem with AI right now is retrieval augmented generation (RAG) with wide-ranging heterogeneous information.  A common architecture pattern in AI right now is that you connect up a large amount of data to an AI model, and when a user or machine sends in a query, you find the best matches from the underlying data set and then send that information to the AI model to answer the user's prompt.  This is a very efficient way to be able to have an AI access information that is frequently changing (like web data) or potentially wouldn't be appropriate to have in an underlying training set of the AI model (like private corporate data). This is a relatively fundamental and breakthrough architecture in AI, but there's a small catch.  The AI's answer is only as good as the underlying information that you serve it in the prompt.  And because the user isn't the one giving it the data, but instead a computer, you're at the mercy of how good that computer is at finding the right information to give the AI to answer the question.  Which means, of course, you're also at the mercy of how good, accurate, up-to-date, and authoritative your underlying information is that you're feeding the AI model in the prompt. Let's take a very basic example.  Say you ask an AI that's connected to the web, "who are the top movie studio heads right now?".  The issue is that there's not many authorative webpages on the internet that are the singular list of movie studio heads *right now* (or for any esoteric topic for that matter).  A human would do lots of browsing, compare answers between sites, check corporate webpages, and more just to decide an answer.  With AI, we're often at the mercy of a search engine going across the web and trying to find various articles and determining their accuracy and authoritativeness to try and eventually find enough information to produce an answer.  Chances are some of those articles are out of date within a year or even were wrong to begin with, but the AI has no reason to know that -- so it will still use that information in its underlying prompt, and lo and behold it can produce an inaccurate answer. The challenge also occurs on smaller data sets, as well.  Imagine an AI assistant that has access to all of your documents, emails, and calendar, and you ask a simple question like "what was last quarter's revenue?"  Not only does the AI have to figure out how to assess the information that is tied specifically to "last quarter", but also it has to wrangle the possibly conflicting information in your underlying data.  You may have an email that had early -but not verified- revenue results, that are different from draft documents that the finance team created, which are different yet again from the final documents with the results.  AI is still quite constrained in its "intelligence" to be able to triage these conflicting answers *today* to produce an accurate result, no matter how confident it sounds. There are some awesome efforts to try and solve this problem, and it's clear this will continue to become less and less of an issue.  With Box AI, to address this challenge, we just launched a new feature in beta called Box Hubs.  With Hubs, users pre-curate content that is the "authoritative" source of truth for particular topics and information -- say for instance, Sales materials, HR documents, or R&D files.  When you ask an AI question in a Hub, you are aiming that question at the most up-to-date and relevant information for that topic.   In our early testing and rolling out it dramatically reduces the issue of getting confusing data, and delivers more accurate answers. I'm excited to see many other breakthroughs in this space -- from better ways of organizing the web over time to AI agents that can fully browse the web and do more of the "research" that a human would when finding information.

Mini-pod w Dr. David Maron - Stanford Director of Preventative Cardiology & renowned expert in heart health. He knows you should run not walk to get your Calcium CT scan. $150 and 30 mins can save your life. Mini-pod 2 discusses how to treat a positive result. 🤍🤍🙏🏼@BG2Pod

@ejkalafarski Live it up!!!!

Yes I’m a fan of being served your wine through a medieval window, aka buchette del vino.

@CommerceJohn Interesting externality of using LLMs. What % of Google searches have they replaced for you?

When I am forgetful, I prompt myself with context and surrounding concepts. I suspect prompting LLMs is improving my self prompts.

@WaterFireProv Leave the kids with the sitter...just do it!

Calling all husbands in the #Boston and #Providence areas! The @WaterFireProv schedule just came out and, for the next few hours, you have your pick of the best restaurants to book for a date night to remember with your spouse. waterfire.org/schedule/2024-…

@ejkalafarski That's Americana at its best

Late post, but loved experiencing Opening Day at Fenway for the first time on Tuesday. #redsox

@eyyyyitsrachel @public Yea, we're good! Question -- I see you closing down a bunch of the alts over time. Is there a plan to sunset the rest? Wondering how much time I may have to grab rare sneaker shares before it sunsets.

@JohnnyStartup @public should be resolved! DM if you have any more issues

@public are you having trouble doing bid/ask matching on alts right now?

I've been avoiding the @MBTA red line like the plague since I started working in Davis Square. Say to myself today, "it's only 2 stops to my lunch in Harvard Square. What could go wrong?"

@KyleGross_ Just a bunch of VCs realizing markups aren't a given...and this game is actually hard in a non-zero interest rate environment...