Tech
Open or closed AI? Learn what to build on at Disrupt 2026
For AI startups, choosing a model isn’t necessarily a one-time architecture decision anymore.
Open models are improving. Frontier APIs keep advancing. Models can be customized for specific workloads, and some companies are building products that use multiple models rather than committing to one. That gives founders more ways to build — and more decisions about where to spend, what to own, and how much flexibility to preserve as the technology changes.
At TechCrunch Disrupt 2026, four conversations approach those decisions from different points in the AI stack, from multi-model applications and customized models to infrastructure and the chips underneath them.
Secure your Disrupt pass to hear how AI leaders are navigating those choices. Save up to $100 on your pass now and get a second pass at 50% off. Or for a limited time, get a $75 Expo+ Pass if you’ve been affected by a layoff.
When one AI model isn’t enough
Choosing between open and proprietary models assumes a company needs to choose one in the first place. Increasingly, AI products can call on different models for different jobs.
The session “The Real Tokenmaxxing: How the Best AI Companies Navigate a Multi-Model World” will bring together Mo Jomaa, partner at CapitalG; Vipul Ved Prakash, co-founder and CEO of Together AI; and Zuzanna Stamirowska, CEO and co-founder of Pathway, on the Builder’s Stage.
They’ll explore why companies are using multiple models; how they balance cost, performance, and flexibility; and when open models can outperform proprietary alternatives.

For founders, that flexibility can affect more than model performance. It can influence operating costs, product decisions, and how quickly a company can take advantage of better models as they emerge.
Get your ticket to Disrupt to hear how companies are deciding which model makes sense for which job. Grab yours now to save up to $100 and get a second pass at 50% off.
How much of your AI stack should you own?
Model choice also raises a bigger question: What does your company need to own?
Manos Koukoumidis, CEO and co-founder of Oumi, will take the Real World AI Stage for “Which AI Should Your Company Actually Deploy: Rent, Customize, or Build.” He’ll tackle whether startups should build their own models, when customization can become a competitive advantage, and how to choose between open and proprietary AI.
Through audience polls, startup scenarios, and a practical framework, Koukoumidis will help attendees evaluate frontier APIs, customized open weights, and owning AI outright. Attendees will come away with three decision principles they can bring to their next architecture conversation.
The choice founders make can shape both the product and the business behind it. Building more of the AI stack can offer greater control and differentiation, but it can also require more time, talent, and resources than relying on existing models.
Add the Oumi session to your Disrupt agenda for a practical framework for deciding how much of your AI stack your company really needs to own. Grab your pass now to sit front row in this discussion.
Where open and proprietary AI fit
For some startups, the decision will still come down to the trade-offs between open and proprietary models.
Nader Khalil, Director of Developer Tech at Nvidia, and Sydney Sykes, Global Head of VC Partnerships at Nvidia, will take the Builders Stage for “Building AI Startups Worth Betting On.” They’ll examine what founders are choosing today, the trade-offs between frontier APIs and open-weight models, and how those choices can affect product strategy and long-term differentiation.

Those trade-offs have business consequences. Model choice can shape everything from costs and infrastructure requirements to how much control they have over their product. It can also determine where — and how easily — a startup can create differentiation competitors can’t replicate.
Secure your Disrupt pass to hear how builder and venture perspectives are shaping model decisions. Save up to $100 on your pass and get a second at 50% off.
When architecture reaches the hardware
Model architecture is only part of the equation. AI performance ultimately depends on the hardware underneath it, and advances in AI are beginning to change how that hardware gets designed.
Anna Goldie, founder and CEO of Ricursive Intelligence, and Azalia Mirhoseini, founder and CTO, will take that idea to the Disrupt Stage in “When AI Starts Designing Its Own Hardware.” They’ll explore how AI is optimizing chips and hardware, why model architecture and hardware are becoming more closely connected, and what an increasingly open AI ecosystem could mean for the infrastructure underneath it.

For founders, the connection between AI and hardware could affect how quickly new capabilities reach the market. Faster chip development could also change the infrastructure available to startups building the next generation of AI products.
Get your ticket to Disrupt to hear what happens when AI starts helping design the hardware that powers it.
Learn how to keep your AI options open at Disrupt 2026
These conversations are part of 200+ sessions across six industry stages, roundtables, and breakouts at Disrupt, taking place October 13-15 at Moscone West in San Francisco. More than 10,000 founders, investors, operators, and tech leaders are expected, along with 250+ speakers and 300+ exhibiting startups.
In addition, matchmaking, dealmaking, and ad hoc networking give attendees opportunities to connect with founders, investors, potential partners, and other builders facing many of the same technology and business decisions.
A startup may use a frontier API today, customize an open model tomorrow, or eventually move workloads among several models. Preserving flexibility could be as important as choosing the right model now.
Secure your pass to TechCrunch Disrupt 2026 and hear how AI leaders are approaching the choices shaping what — and how — they build. Save up to $100 now and get 50% off a second pass. Laid off? Grab your Expo+ Pass at just $75.

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Tech
Hot Girl Hotline is like ‘Dear Abby’ for the AI era
Women throughout history have always sought out relationship advice, whether from newspaper columnists like “Dear Abby,” letters to Cosmo, or just chatting with girlfriends. In the social media era, you can instead post anonymously on Reddit relationship forums or look to social media creators who discuss the topic.
Now, two sisters are launching a startup for young women, Hot Girl Hotline, which focuses on bringing AI into these conversation.
I know what you may be thinking: With all the advances in AI technology, founders are building something for women to talk about their dating woes? Well…yes!
The reality is that people have already been turning to large language models (LLMs) via apps like ChatGPT for this type of advice, and the team believes this type of activity should be handled more carefully.
Unfortunately, as we’ve seen, chatting with a general-purpose chatbot about personal topics can sometimes lead to disastrous effects — especially for those who were already mentally fragile. ChatGPT, for example, has faced a wave of lawsuits over its alleged manipulative conversation tactics that plaintiffs say contributed to negative mental health effects, and, in some cases, suicide.
The idea behind Hot Girl Hotline is to reach young women who are looking to have these sorts of private conversations while navigating dating life and relationships, but in a safer way.
“We’re not trying to be an AI companion,” explained Balia Mudgil, formerly a social media consultant, who co-founded the startup with her sister Sumrin (“Sumi”), who studied computer science at Stanford. “A companion is really going after solving loneliness, escapism, boredom — and you can rely on a lot of emotional dependency from that AI companion.”

Balia says the startup’s approach is to focus on offering quality advice grounded in behavioral science, but in a way that makes it feel like you’re chatting with a trusted friend or big sister. The conversation is often Socratic, with the AI asking you questions to help you arrive at the answer yourself.
“This is not to replace speaking to a human. This is not clinical advice, and we have a lot of safeguards in place…we take safety really seriously,” Baila said. If conversations raise flags, for instance, the user is referred to resources such as the crisis hotline 988.
“We believe the key to quality advice is not just knowing what to do next; it’s understanding why you’re doing it. So that’s a big piece of it,” added Sumi.
Notably, the AI also knows when to end the conversation; it doesn’t keep asking follow-up questions to drag you further down a rabbit hole. Instead, it pushes users to go take action out in the real world rather than ruminate on the problem.

The sisters believe there’s room for an app like this because not everyone wants to post on the web for advice, and there are times when you don’t want to bring up a personal, dating, or relationship-focused issue with a friend.
Friends can bring their own biases into the conversation, or the user may not want to put their partner on blast for something they did before they determine whether they’re going to work through it or end the relationship.
“It doesn’t mean you’re replacing your friend — you’re just trying to get another perspective,” says Balia of the hotline.

The app also personalizes its advice for each user to reflect their values, goals, identity, and tastes.
Under the hood, the startup relies on a mix of AI models and encrypts users’ data in transit and at rest. It doesn’t sell or train on the data, either. When it uses a third-party AI model, it follows a zero-data-retention policy there as well.
Hot Girl Hotline plans to monetize through a $9.99 per month subscription, which hundreds of its most active users are already paying for. Later, it may incorporate ads, too.
Relationship advice is just the beginning of how the company wants to cater to young women. It also plans to expand into other areas, like beauty and lifestyle.
New York-based Hot Girl Hotline is currently bootstrapped and will be participating in TechCrunch Disrupt’s upcoming Startup Battlefield 200. It’s available on iOS and the web.
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Tech
5 startups that caught VCs’ attention at the latest PearX demo day
There isn’t a shortage of accelerators for startups, but one of the few that investors watch closely is PearX, a 12-week program that caps its cohorts at a mere 20 startups and is run by Pear VC, a pre-seed and seed-focused venture firm.
PearX’s bi-annual demo day is consistently attended by top venture capitalists, reflecting the historically strong caliber of companies in each batch. Some of the startups that came out of recent cohorts include Known, which uses voice AI to match people for dates and secured funding from Forerunner Ventures. Another is Andera, a startup that automates corporate audit and compliance tasks and raised a $37 million Series A from Lightspeed this summer.
The PearX program distinguishes itself from Y Combinator, the OG of startup accelerators, in several ways. Besides being much smaller, it doesn’t offer companies standard terms. It’s investments can be as high as $2 million. Moreover, unlike YC, where some of the buzziest startups raise funding before the program ends, PearX claims to keep its participants under wraps until demo day.
TechCrunch attended Pear’s latest demo day, which took place in San Francisco last week, and then stuck around to ask some of the VCs about which companies stood out to them out of the 16 startups in the batch.
Below are five of the companies that seemed to have generated the most buzz.
What it does: Spatial foundational models for powering robotics, gaming, and special effects.
Why it stood out: While Speridlabs is certainly not the only startup developing world models to do for 3D space what LLMs did for language, it argues that its more established competitors, including Runway, Odyssey, and Google’s Genie, cannot be queried or modified. To solve this, Speridlabs built Mundus, which it calls a 3D Midjourney because it keeps its geometry persistent when a part is changed.
What it does: building a fast, cost-efficient chip that runs inference directly on device.
Why it stood out: Nvidia’s GPUs and Google’s TPUs require expensive, power-hungry memory that is currently in short supply. Saia claims to have designed a chip that bypasses traditional memory by running AI directly out of flash storage. The startup claims its chip delivers vastly superior speeds and eight times the capacity while using four times less power than Nvidia’s Jetson, a leading local AI chip and board. Saia says it’s already in discussions with Samsung regarding memory integration, plans to start fabricating test chips next year, and aims to launch mass production by 2028. Developing hardware is notoriously brutal, but 20-year-old founder Ayaan Govil managed to convince Pear VC co-founder Mar Hershenson, a semiconductor engineer with a PhD in circuit design, to take a chance on his vision.
What it does: a more secure AI personal assistant.
Why it stood out: Ren claims to offer functionality similar to Muse and Instinct, but with a heavy focus on security and privacy. The startup says it keeps data on-device where possible or uses a secure private cloud, checking actions against strict user-set guardrails. Furthermore, Ren distinguishes itself from competitors that rely on human operators to place phone calls by using a fully automated voice system, keeping human involvement entirely out of the loop to protect user privacy.
What it does: AI native trust and estate planner.
Why it stood out: Setting up a trust is expensive and time-consuming. Veros wants to simplify the work normally done by attorneys, wealth managers, and trust administrators by employing AI to recommend structures and manage assets over their lifetime. Already managing $250 million in AUM, the startup is also in the process of securing a trust charter so it can operate as a regulated trust company itself.
What it does: AI engineer for industrial design.
Why it stood out: Datum wants to expedite physical product development by helping engineers find and use what they built previously. The startup indexes a company’s library of 3D designs. Using proprietary Geometric Fingerprint technology, Datum identifies parts based on their shape, helping streamline and automate engineering across a massive physical design market.
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Tech
Pixel 12 Leak Suggests Google Has Bigger Plans for Its Next Fold
Pixel 12 records list four models, with new display details and a dual-glass Fold prototype that could reduce the crease on Google’s next foldable.
The post Pixel 12 Leak Suggests Google Has Bigger Plans for Its Next Fold appeared first on TechRepublic.
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