Meet the new Audience Choice winners to lead breakouts at TechCrunch Sessions: AI
You voted. They rose to the top!
Meet the two Audience Choice winners who'll take the breakout stage at TechCrunch Sessions: AI on June 5 in Zellerbach Hall at UC Berkeley to share their insights with 1,200 AI leaders and enthusiasts.
We sifted through hundreds of Call for Content submissions and narrowed them down to six standout finalists. Your votes crowned two winners — and now they're ready to share their cutting-edge AI insights live.
Yann Stoneman, staff solutions architect at Cohere: Behind Your Firewall: Secure Generative AI for Regulated Enterprises
Hua Wang, executive director at Global Innovation Forum: The AI Policy Playbook: What Global Startups Need to Know
Session: Ever wonder how to use cutting-edge generative AI in healthcare or finance — without sweating over data privacy? Join Yann for a lively breakout session at TC Sessions: AI. Alongside three expert panelists, Yann will guide an interactive, 50-minute conversation packed with real-world use cases from Cohere's North (agentic AI workspace) and Compass (multimodal retrieval). You'll get practical strategies for deploying secure, customized AI models on your own infrastructure — no external cloud required. Expect hands-on demos, live Q&A, and insights that'll help you build AI solutions safely and confidently, right behind your firewall.
About Yann Stoneman: Yann Stoneman is a staff solutions architect at Cohere, where he helps enterprises deploy secure, customizable AI powered by next-gen foundation models. Previously at AWS, he supported large-scale AI adoption and debuted an AI demo at re:Invent 2023. Yann is a trusted partner for seamless integration and user-friendly AI design. His expertise has been featured at Generative AI World and Voices of Data Science, and on the blogs of Cohere and AWS. He holds a BA from the Juilliard School.
Session: AI gives startups an edge, but regulation can slow them down. This breakout dives into how founders can stay compliant and competitive while scaling globally. Learn how to tap into AI tools for digital trade, navigate evolving data laws, and unlock new markets. We'll cover the policies shaping the future of AI startups and offer real-world strategies to help you expand without the red tape. If you're building, investing in, or regulating AI, this session delivers the insights you need to lead with confidence.
About Hua Wang: Hua leads the Global Innovation Forum (GIF), where she builds bridges between diverse entrepreneurs and the global economy. At GIF, she drives inclusive strategies for trade and digital policy, partnering with business leaders, nonprofits, and international institutions like the World Trade Organization and the UN to unlock global opportunities for underrepresented voices.
From launching a telemedicine startup to helping startups raise $20 million+ as an accelerator director, Hua's career spans entrepreneurship, law, tech, and policy. She's also served as an entrepreneur-in-residence across Chile, Malaysia, and the U.S. A former attorney and banker, Hua holds degrees from Duke and Northwestern Law — and a deep belief in innovation as a driver of global growth.
AI is moving fast — and so should you. Learn how to build behind your firewall with Yann Stoneman and unlock global markets with Hua Wang — two of the audience-chosen breakout leaders you won't want to miss. Save up to $210 on your pass, or bring a crew and save even more. Head to the agenda to see what's in store and grab your ticket before prices jump.
Go beyond attending — exhibit your brand and innovation in front of 1,200 top AI minds. Space is limited, so don't miss your chance to make an impact! Grab your exhibit table here before they run out.
Or, explore more sponsorship opportunities and activations at TC Sessions: AI. Get in touch with our team by filling out this form.
Subscribe to the TechCrunch Events newsletter for early access to special deals and the latest event news.
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
WIRED
an hour ago
- WIRED
Vibe Coding Is Coming for Engineering Jobs
Jun 12, 2025 6:30 AM Engineering was once the most stable and lucrative job in tech. Then AI learned to code. Photo-Illustration:On a 5K screen in Kirkland, Washington, four terminals blur with activity as artificial intelligence generates thousands of lines of code. Steve Yegge, a veteran software engineer who previously worked at Google and AWS, sits back to watch. 'This one is running some tests, that one is coming up with a plan. I am now coding on four different projects at once, although really I'm just burning tokens,' Yegge says, referring to the cost of generating chunks of text with a large language model (LLM). Learning to code has long been seen as the ticket to a lucrative, secure career in tech. Now, the release of advanced coding models from firms like OpenAI, Anthropic, and Google threatens to upend that notion entirely. X and Bluesky are brimming with talk of companies downsizing their developer teams—or even eliminating them altogether. When ChatGPT debuted in late 2022, AI models were capable of autocompleting small portions of code—a helpful, if modest step forward that served to speed up software development. As models advanced and gained 'agentic' skills that allow them to use software programs, manipulate files, and access online services, engineers and non-engineers alike started using the tools to build entire apps and websites. Andrej Karpathy, a prominent AI researcher, coined the term 'vibe coding' in February, to describe the process of developing software by prompting an AI model with text. The rapid progress has led to speculation—and even panic—among developers, who fear that most development work could soon be automated away, in what would amount to a job apocalypse for engineers. 'We are not far from a world—I think we'll be there in three to six months—where AI is writing 90 percent of the code,' Dario Amodei, CEO of Anthropic, said at a Council on Foreign Relations event in March. 'And then in 12 months, we may be in a world where AI is writing essentially all of the code,' he added. But many experts warn that even the best models have a way to go before they can reliably automate a lot of coding work. While future advancements might unleash AI that can code just as well as a human, until then relying too much on AI could result in a glut of buggy and hackable code, as well as a shortage of developers with the knowledge and skills needed to write good software. David Autor, an economist at MIT who studies how AI affects employment, says it's possible that software development work will be automated—similar to how transcription and translation jobs are quickly being replaced by AI. He notes, however, that advanced software engineering is much more complex and will be harder to automate than routine coding. Autor adds that the picture may be complicated by the 'elasticity' of demand for software engineering—the extent to which the market might accommodate additional engineering jobs. 'If demand for software were like demand for colonoscopies, no improvement in speed or reduction in costs would create a mad rush for the proctologist's office,' Autor says. 'But if demand for software is like demand for taxi services, then we may see an Uber effect on coding: more people writing more code at lower prices, and lower wages.' Yegge's experience shows that perspectives are evolving. A prolific blogger as well as coder, Yegge was previously doubtful that AI would help produce much code. Today, he has been vibe-pilled, writing a book called Vibe Coding with another experienced developer, Gene Kim, that lays out the potential and the pitfalls of the approach. Yegge became convinced that AI would revolutionize software development last December, and he has led a push to develop AI coding tools at his company, Sourcegraph. 'This is how all programming will be conducted by the end of this year,' Yegge predicts. 'And if you're not doing it, you're just walking in a race.' The Vibe-Coding Divide Today, coding message boards are full of examples of mobile apps, commercial websites, and even multiplayer games all apparently vibe-coded into being. Experienced coders, like Yegge, can give AI tools instructions and then watch AI bring complex ideas to life. Several AI-coding startups, including Cursor and Windsurf have ridden a wave of interest in the approach. (OpenAI is widely rumored to be in talks to acquire Windsurf). At the same time, the obvious limitations of generative AI, including the way models confabulate and become confused, has led many seasoned programmers to see AI-assisted coding—and especially gung-ho, no-hands vibe coding—as a potentially dangerous new fad. Martin Casado, a computer scientist and general partner at Andreessen Horowitz who sits on the board of Cursor, says the idea that AI will replace human coders is overstated. 'AI is great at doing dazzling things, but not good at doing specific things,' he said. Still, Casado has been stunned by the pace of recent progress. 'I had no idea it would get this good this quick,' he says. 'This is the most dramatic shift in the art of computer science since assembly was supplanted by higher-level languages.' Ken Thompson, vice president of engineering at Anaconda, a company that provides open source code for software development, says AI adoption tends to follow a generational divide, with younger developers diving in and older ones showing more caution. For all the hype, he says many developers still do not trust AI tools because their output is unpredictable, and will vary from one day to the next, even when given the same prompt. 'The nondeterministic nature of AI is too risky, too dangerous,' he explains. Both Casado and Thompson see the vibe-coding shift as less about replacement than abstraction, mimicking the way that new languages like Python build on top of lower-level languages like C, making it easier and faster to write code. New languages have typically broadened the appeal of programming and increased the number of practitioners. AI could similarly increase the number of people capable of producing working code. Bad Vibes Paradoxically, the vibe-coding boom suggests that a solid grasp of coding remains as important as ever. Those dabbling in the field often report running into problems, including introducing unforeseen security issues, creating features that only simulate real functionality, accidentally running up high bills using AI tools, and ending up with broken code and no idea how to fix it. 'AI [tools] will do everything for you—including fuck up,' Yegge says. 'You need to watch them carefully, like toddlers.' The fact that AI can produce results that range from remarkably impressive to shockingly problematic may explain why developers seem so divided about the technology. WIRED surveyed programmers in March to ask how they felt about AI coding, and found that the proportion who were enthusiastic about AI tools (36 percent) was mirrored by the portion who felt skeptical (38 percent). 'Undoubtedly AI will change the way code is produced,' says Daniel Jackson, a computer scientist at MIT who is currently exploring how to integrate AI into large-scale software development. 'But it wouldn't surprise me if we were in for disappointment—that the hype will pass.' Jackson cautions that AI models are fundamentally different from the compilers that turn code written in a high-level language into a lower-level language that is more efficient for machines to use, because they don't always follow instructions. Sometimes an AI model may take an instruction and execute better than the developer—other times it might do the task much worse. Jackson adds that vibe coding falls down when anyone is building serious software. 'There are almost no applications in which 'mostly works' is good enough,' he says. 'As soon as you care about a piece of software, you care that it works right.' Many software projects are complex, and changes to one section of code can cause problems elsewhere in the system. Experienced programmers are good at understanding the bigger picture, Jackson says, but 'large language models can't reason their way around those kinds of dependencies.' Jackson believes that software development might evolve with more modular codebases and fewer dependencies to accommodate AI blind spots. He expects that AI may replace some developers but will also force many more to rethink their approach and focus more on project design. Too much reliance on AI may be 'a bit of an impending disaster,' Jackson adds, because 'not only will we have masses of broken code, full of security vulnerabilities, but we'll have a new generation of programmers incapable of dealing with those vulnerabilities.' Learn to Code Even firms that have already integrated coding tools into their software development process say the technology remains far too unreliable for wider use. Christine Yen, CEO at Honeycomb, a company that provides technology for monitoring the performance of large software systems, says that projects that are simple or formulaic, like building component libraries, are more amenable to using AI. Even so, she says the developers at her company who use AI in their work have only increased their productivity by about 50 percent. Yen adds that for anything requiring good judgement, where performance is important, or where the resulting code touches sensitive systems or data, 'AI just frankly isn't good enough yet to be additive.' 'The hard part about building software systems isn't just writing a lot of code,' she says. 'Engineers are still going to be necessary, at least today, for owning that curation, judgment, guidance and direction.' Others suggest that a shift in the workforce is coming. 'We are not seeing less demand for developers,' says Liad Elidan, CEO of Milestone, a company that helps firms measure the impact of generative AI projects. 'We are seeing less demand for average or low-performing developers.' 'If I'm building a product, I could have needed 50 engineers and now maybe I only need 20 or 30,' says Naveen Rao, VP of AI at Databricks, a company that helps large businesses build their own AI systems. 'That is absolutely real.' Rao says, however, that learning to code should remain a valuable skill for some time. 'It's like saying 'Don't teach your kid to learn math,'' he says. Understanding how to get the most out of computers is likely to remain extremely valuable, he adds. Yegge and Kim, the veteran coders, believe that most developers can adapt to the coming wave. In their book on vibe coding, the pair recommend new strategies for software development including modular code bases, constant testing, and plenty of experimentation. Yegge says that using AI to write software is evolving into its own—slightly risky—art form. 'It's about how to do this without destroying your hard disk and draining your bank account,' he says.
Yahoo
an hour ago
- Yahoo
Multiverse Computing raises $215M for tech that could radically slim AI costs
On Thursday, Spanish startup Multiverse Computing announced that it raised an enormous Series B round of €189 million (about $215 million) on the strength of a technology it calls 'CompactifAI.' CompactifAI is a quantum-computing inspired compression technology that is capable of reducing the size of LLMs by up to 95% without impacting model performance, the company says. Specifically, Multiverse offers compressed versions of well-known open source LLMs – primarily small models – such as Llama 4 Scout, Llama 3.3 70B, Llama 3.1 8B, Mistral Small 3.1. However, it will soon release a version of DeepSeek R1, with more open source and reasoning models coming soon. Proprietary models from OpenAI and others are not supported. It's 'slim' models, as the company calls them, are available on Amazon Web Services or can be licensed for on-premises uses. The company says its models are 4x-12x faster than the comparable not-compressed versions, which translates to 50%-80% reduction in inference costs. For instance, Multiverse says that its Lama 4 Scout Slim costs 10 cents per million tokens on AWS compared to Lama 4 Scout's 14 cents. The company says that some of its models can be made so small and energy efficient they could be run on PCs, phones, cars, drones and even the DIY-enthusiast's favorite tiny PC, Raspberry PI. (We are suddenly imagining those fantastical Raspberry PI Christmas-light houses upgraded with LLM-powered interactive talking Santas.) Multiverse has some technical might behind it. It was co-founded by CTO Román Orús, a professor at the Donostia International Physics Center in San Sebastián, Spain. Orús is known for his pioneering work on tensor networks (not to be confused with all AI-related things named Tensor at Google). Tensor networks are computational tools that mimic quantum computers but run on classic computers. One of their primary uses these days is compression of deep learning models. Multiverse's co-founder and CEO, Enrique Lizaso Olmos, also holds multiple mathematical degrees and has been a college professor. He spent most of his career in banking, best known as the former deputy CEO of Unnim Bank. The Series B was led by Bullhound Capital (which has backed companies like Spotify, Revolut, DeliveryHero, Avito, Discord) along with participation of HP Tech Ventures, SETT, Forgepoint Capital International, CDP Venture Capital, Santander Climate VC, Toshiba and Capital Riesgo de Euskadi – Grupo SPR. Multiverse says it has 160 patents and 100 customers globally, including Iberdrola, Bosch, and the Bank of Canada. With this funding, it has raised about $250M to date. Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Yahoo
14 hours ago
- Yahoo
RiverMeadow Expands Global Reach with Launch in AWS Mexico (Central) Region
LOS GATOS, Calif., June 11, 2025 /PRNewswire/ -- RiverMeadow Software Inc, a leader in workload mobility automation, is excited to announce the availability of its Workload Mobility Platform in the AWS Mexico (Central) Region, marking another key milestone in the continued strategic global expansion alongside AWS's extensive infrastructure. This development supports RiverMeadow's mission to provide seamless, scalable, and secure migration capabilities to customers worldwide, while strengthening the growing presence in Latin America. The AWS Mexico (Central) Region provides customers with greater flexibility to run workloads and securely store data in Mexico, improving performance with lower latency. The new AWS Region supports developers, startups, entrepreneurs, public and private sector organizations, as well as industries such as education, entertainment, financial services, healthcare. This new region gives customers greater choice for running their applications and services from the AWS data centers located in Mexico, enabling alignment with regional compliance and data sovereignty standards. RiverMeadow's commitment extends across Mexico, with tailored support now available in multiple key AWS regions. This continued growth reflects the dedication to deliver end-to-end Workload Mobility Solutions wherever organizations need to operate. "The recent momentum in Latin America, particularly in Mexico, is significant," said Justin Yunag, Chief Revenue Officer of RiverMeadow. "Our workload mobility platform is uniquely positioned to help customers take full advantage of the new Mexico region by delivering fully automated migration, modernization and optimization of workloads moving to AWS". Why Migrate to AWS Mexico with RiverMeadow? Rapid Time to Value – Begin migrating workloads in as little as 30 minutes, accelerating ROI from day one. Solution Flexibility – Migrate complex environments across hosted and private platforms with full VM and OS flexibility. Scalability – Enable rapid migrations at scale through a decoupled data transfer architecture. Integrated Automation – Shorten migration timelines with integrated and custom automation. Derisked Migrations – Minimize source impact and accelerate acceptance testing. Cost Reduction – Reduce operational expenses by eliminating technical debt. AWS's ISV funding program available in region to reduce overall migration costs. Discover the advantages of AWS Mexico by leveraging RiverMeadow's trusted Workload Mobility Platform. Whether you're expanding into Mexico, looking to mitigate rising costs from Broadcom pricing changes or simply transitioning away from current hosting/cloud providers, RiverMeadow can help. About RiverMeadowRiverMeadow provides multi-cloud and hybrid-cloud workload mobility solutions that automate the migration and modernization of existing workloads to any cloud or virtualized environment. With a proven track record across complex enterprise transformations, RiverMeadow is the trusted partner for organizations navigating modernization at scale. Media ContactFlor de Maria Vazquez - Director - Sales OperationsRiverMeadow Software flor@ View original content to download multimedia: SOURCE RiverMeadow Software Inc.
