AI + Consumer Entertainment @bitkraftVC
Joined March 2013
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This weekend I found myself completely lost in vibecoding what I've always wanted to build: A Diablo-like, 2.5D isometric fantasy dungeon crawler (I am not known for my originality)
I used @cursor_ai as the IDE and alternated between @grok and Claude Sonnet to build out the code and debug whenever either got stuck. I have zero coding knowledge and this was candidly quite daunting before I started, but when I did start I found the hours whizzing past. I also found myself really enjoying the experience, which is nice. It felt like finding a new hobby.
I highly recommend people give this a whirl. The possibilities are limitless and the future is very very bright. All you need is curiosity, willpower, and patience!
jonathan huang retweeted
Everyone has a story of missed investment riches.
Agents promise to fix that. After building systems across prediction markets, crypto, perps and stocks, we think most won’t... yet.
"10 hard problems in agentic investing" (written w/ @SpinFN)
Thread + bitkraft.vc/insights/10-hard…
jonathan huang retweeted
I always find it surprising when VCs in new tech waves get overly hung up on business quality / metrics (TAM, quality of revenue, margin, etc.).
Disruptive tech always precedes figuring out the business model. Hell, we didn't monetize the Internet for years.
there are actions which people value/ don't value, and I think AI adopts best when the latter is removed; shopping itself is fundamentally valuable to ppl (phantom shopping sites) and humans want to enjoy the dopamine hit it confers. maybe works for mundane stuff like groceries
jonathan huang retweeted
this meeting could have been an MCP invoked search of our company’s internal knowledge base that aggregates data from virtually every service we use behind a unified retrieval layer and provides a streamlined interface for extracting critical business insights
So proud of @DaniKTran who penned this! Every technological wave has spawned new hardware form factors which in turned leveraged new technological formats to produce net-new categories of consumer entertainment (PC, Console, Mobile, etc). Any investor can say that - it takes a great one to outline why it really is different this time
Give this a read and Dani a follow!
Easier to build. Harder to sell. 🔧
Our Principal @DaniKTran the AI hardware gap, why capital didn't save Magic Leap, Jawbone, Humane or Amazon Halo, and the five questions we ask before we back one.
🔗 bitkraft.vc/insights/the-har…
jonathan huang retweeted
Today, we are introducing Inkling.
Inkling reasons efficiently across text, image, and audio modalities. We are making the full weights available.
thinkingmachines.ai/news/int…
Available today for fine-tuning on Tinker. Play with it in the Inkling Playground. 🧵
every investor can attest to how daunting it is to invest into AI apps today. I’ve looked at a lot of agentic AI products this year and all of them are new apps asking for a slice of your attention
Acti is the only one that is going the other way: it disappears into the keyboard you already use. No app to open, no context to re-paste. Long-press ANY key, and it invokes AI
That inversion is why we backed @openacti1 on their journey to become the next category defining business
so excited for ACTI and @callmeyoung93!!
The last major keyboard moment was in 2007,
when Apple put the keyboard on glass.
Nearly 20 years later, we're introducing:
Acti @openacti1, the Agentic Keyboard.
Not another AI keyboard that fixes grammar.
Not another voice keyboard that types faster.
An invisible agent in every text field.
It doesn't predict your next word.
It takes your next action. 👇
jonathan huang retweeted
Mira Murati says human-AI collaboration needs models that can listen while they think:
"The types of models that we work with today, they're very turn-based. You talk, they talk, then they go off and think."
"While they're thinking, it's almost like they're deaf and blind. They cannot perceive anything else about what's going on."
"By contrast, our interactions with each other are very rich. There is a lot of information in our interactions when we are silent, when we're thinking, when we're interrupting one another."
"Interaction models are able to capture all of this nuance. They're not turn-based. They're more like time-based interaction, where they're continuously taking in audio, text, video, and continuously providing output."
"This enables you to catch things like interruptions and simultaneous speech, and really create a rich, high bandwidth interaction between humans and machines."
@miramurati at Bloomberg Tech live with @emilychangtv
jonathan huang retweeted
The fall is so stupid
U don't really need 1.5TB per CPU for training, chatbot interactions, and light agentic workloads
Provisioning that much DRAM for them will just lead to underutilization and waste of resources (500GB-750GB per CPU is enough)
My biggest fear was Nvidia being unable to sell finished Rubin NVL72 racks becuz of the DRAM shortage
Now they can handle demand in a much better way
there is a classic venture heuristic that revolutionary products tend to start out looking like toys, but it is increasingly clear to me that this framework is breaking down in real time because of a quality that AI confers to the reality we live in: time compression
this generation of founders no longer have the luxury of time on their side to incubate a toy and slowly build it into a platform anymore
the traditional playbook, and when i say “traditional” i am referring to the AI thought pieces from the *distant* 2024/2025, revolved around find a wedge that is 1000x better than incumbents, then systematically verticalize
I’d argue you’re probably going to be way too slow if you are building that way
i think winning this race requires teams that have the right constellation of capabilities to build from the terminal state from day 1
which capabilities you ask? read this longer piece from the indelible @SpencerMa_ on world models to find out
DMs open if you are one of those teams
jonathan huang retweeted
I've always been passionate about games and they've played a big part in @GoogleDeepMind’s history, as the perfect proving ground for AI. Thrilled to announce this research partnership with @FenrisCreations - @EveOnline is one of the most extraordinary games ever built and has an amazing community. Very excited to work with @HilmarVeigar and the team!
jonathan huang retweeted
Career advice nobody told you: You have to demonstrate excellence in everything you do. Your income scales proportional to the amount of excellence that you're able to demonstrate. Strategic incompetence is a lie. You don't get to pick and choose when to show up, because the world will ignore your best and judge you for your worst. Everything matters. Every single thing. Top performers show up with energy and enthusiasm for the little things just as much as they do for the big things. If you're in the top-10% of performers, there's no ceiling for what you can do. But the self-awareness to identify where you currently stack up, and adapt to the honest feedback on it, is very rare. If you're in the top-10%, you know it. If you're not, figure out why and fix it.
jonathan huang retweeted
Once again, the modern VC industrial complex perpetuates startup short-termism
Businesses that are hard and important, but need time to turn profits, is why VC exists as an instrument (i.e. long term investment with asymmetric upside)
With VCs now incentivized to produce short-term scoreboard results (e.g. markups -> consensus investing) motivated by AUM “prestige”, less and less firms are incentivized to actually bet on something with the view of success on a longer time horizon and instead make investments by underwriting the likelihood a company attracts more investment from someone else in <3 years
jonathan huang retweeted
Indeed, it was *because* I was not from the aerospace industry that SpaceX made such radical breakthroughs. Same for Tesla.
Those in the industry would have if they could have.
In this 2015 interview, the host — a Tsinghua University professor — expressed genuine curiosity about how Elon Musk was able to found SpaceX without prior experience and knowledge in aerospace, especially given that rocket science is one of the most demanding hard sciences — and that Musk was serving as both CEO and CTO.
Musk explained that deep expertise can be built outside formal academic programs — by reading extensively, conducting experiments, and speaking directly with experts in the field.
PSA: this is a prosumer research tool with powerful web crawling capabilities which means it’s great for fundamental, qualitative research but it is by no means going up against BBG terminal (quantitative, tick by tick data, opaque fixed income markets)
apples and oranges..
Perplexity just became the the first Al company to truly go head-to-head with the Bloomberg Terminal...
Using Perplexity Computer (with no local setup or single LLM limitation), it was able to build me a terminal with real-time data to analyze $NVDA using Perplexity Finance:
perhaps my favourite learning about @steipete is him quoting Howard Stark from Iron Man 2. incredible auramogging
ALT A side-by-side two-panel collage. The left panel shows a grainy 1970s-style film reel of Howard Stark from Iron Man 2. The right panel shows a high-definition screenshot of Peter Steinberger in a black t-shirt during an interview on the Lex Fridman podcast. Both images include subtitles at the bottom that read: 'I'm limited by the technology of my time