Gigi Wang

As AI workloads eat up global computing supply, DRAM prices are surging like never before—creating major challenges for teams trying to plan out their data center spend. One of my portfolio companies, Mext, is addressing the largest cost component in the datacenter: server memory (DRAM). From being on the board of Redis for the last twelve years, I’ve learned a lot about the various aspects of this problem and approaches to solving them. Mext found a breakthrough, using new AI techniques, for dramatically reducing the amount of server-DRAM required to run applications, all while maintaining performance. It intelligently manages the server’s memory, keeping hot pages (i.e., those in use by applications) in fast DRAM and offloading cold pages (i.e., those less used) to a much less expensive memory tier (e.g., NVMe Flash). Key to the approach is ensuring cold memory pages that are about to be accessed by an application are back in DRAM before the application needs them or notices that they were gone. This is done without modifications to the application or the OS – so it can run in the cloud or on-premise. Mext thus allows applications to either run using less DRAM or keep their DRAM footprint but do more with it. They're hosting a webinar along with Fred Weber (former CTO of AMD) on Jan 22nd at 10am pacific time. You can register here: https://lnkd.in/gXe9GCeE

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How did a small city like the City of Corona become a surprising innovation hub for AI? In our latest GovAI podcast, I sat down with Chris McMasters, CIO of Corona, California. After nearly two decades in the private sector, Chris made the leap into government—driven by a sense of purpose to serve. Our conversation tackled a big question: why does government often lag in adopting new technologies like AI? Chris explained it’s not about chasing the latest tech—it’s about protecting the people they serve and ensuring any new tool actually makes a difference. The key? Build trust first, then show—not tell—how technology can help. Chris believes AI won’t replace people—it’ll free them to focus on what humans do best. His vision: a future where city services are as seamless as ordering from Amazon, with AI agents removing the red tape. For anyone working in GovTech, or trying to break in, you'll learn a lot from this conversation. 🔗 Check it out here: https://lnkd.in/dzNed-ZP or listen here: https://lnkd.in/dhpwW_-8

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Sanyukta Bhide joined the University of Washington Bothell's Social enterprise class to share her story. After a career in engineering at big companies and start ups, Sanyukta Bhide took a leap into entrepreneurship. This was driven by a personal mission to help families care for aging loved ones. Through the University of Washington’s Women’s Entrepreneurship Program, she launched Mivera Technologies with a focus on tech-enabled senior care. She’s now navigating the tough but exciting early stages: raising capital via crowdfunding, finding the right partners, and defining her brand. The class had so many takeaways including: 💡 Lead with passion. 💡 Expect failure—and learn from it. 💡 Find your people. 💡 Keep investing in yourself. Sanyukta's story is a great reminder that innovation often starts with something personal—and grows through persistence.

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🧠 Great conversation today with Stephen Kwan, during a thoughtful session with fellow International Society of Service Innovation Professionals (ISSIP) colleagues, hosted by the amazing Jim Spohrer at University of California, Santa Cruz – Silicon Valley 🌉💬 We dived deep into one of the most debated (and misunderstood) topics in the AI governance landscape: Regulation vs. Standards 🇪🇺 vs 🇺🇸 🇪🇺 The EU’s approach: proactive, enforceable, and focused on risk prevention – think #AIACT and binding compliance. The idea? Prevent harm before it happens. But it comes at a cost: less flexibility and slower innovation cycles. 🇺🇸 The US model: driven by industry, built on international standards – voluntary but influential. No “teeth” unless linked to legal or market consequences. It doesn’t prevent issues upfront but bets on accountability and post-event enforcement. ⚖️ What’s better? Depends on your goals. Regulation ensures consistency and public trust, but can limit agility. Standards empower innovation but need real consequences to be effective. 👉 The key insight from today: a hybrid model might be the path forward – leveraging the EU’s risk-based guardrails with the US’s dynamic, sector-led adaptability. Thanks to Stephen Kwan, Jim Spohrer, and all the International Society of Service Innovation Professionals (ISSIP) Fellows for the stimulating exchange! 🚀 #AI #Governance #Regulation #Standards #Innovation #TrustworthyAI #ISSIP #DigitalPolicy #SiliconValley #EULaw #ResponsibleAI #TechEthics

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Had a great time at DC Startup & Tech Week (Formerly DC Startup Week) moderating a panel with Scott Christensen (Chesapeake Bay Seed Capital Fund (CBSCF) , Faith Davis (Exelon) and Bill McNulty (NextEra Energy Investments), convened by the great C'pher Gresham. Here's a quick recap: 1) The panelists were phenomenal - a mixture of corporate, state and foundation-backed VC's all focusing on climate. They're actively funding companies across a range of sectors - e.g. nature-based solutions, energy + AI, water, etc. Point being, we were lucky to have experts with such broad purviews. 2) The current climate could be pushing at least some climate VC's to focus on software and move away from hardware, at least temporarily. This type of capital may indeed just be better suited for software companies at this juncture. It also reflects the fact that certain segments of the climate-tech market are just more mature than others - e.g. software performs best once the hardware and the business case around it are solid, then it becomes and optimization and efficiency game. 3) Founders need to target "must-solve" climate problems from the investor lens. In other words, yes there's a sea of climate challenges where startups can be additive. However, in this environment, few of these areas are attracting meaningful capital. There's nothing wrong with tackling problem areas that are under-invested, we need this in spades. However, for those trying to get capital in the door, realize the constraints that come with targeting problems that investors just aren't prioritizing. 4) Look to funders overseas. The EU, where so much climate finance, policy and general expertise has come from, could be playing a much more important role. I'd also argue that Gulf countries like KSA and UAE are going to be critical here too, not to mention China, of course. 5) We need mentoring and coaching to be at an all-time high. With so much uncertainty, networks/communities where both founders and investors can learn from/lean on each other have never been more important. The panel/audience was a nice microcosm of the types of support networks we need to be actively building. Big thanks again to C'pher, Faith, Scott and Bill, as well as the whole DC Startup + Tech Week team. Til next year!

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This woman built tech that can spot bipolar episodes, detect postpartum depression, and keep her diabetic son alive. Vivienne Ming is a theoretical neuroscientist, a serial entrepreneur, and a self-proclaimed “mad scientist.” Her obsession? Maximizing human potential. Vivienne was born Evan Campbell Smith. By her early twenties, she had dropped out of college, fallen into depression, and was contemplating suicide. Then she made a decision: if she was going to keep living, she was going to do something substantial. She flipped a coin between economics and cognitive science. It landed on cognitive science. She went back to UC San Diego, earned a degree in cognitive neuroscience, then completed a PhD in psychology and theoretical neuroscience at Carnegie Mellon. While in grad school, she met Norma, a fellow PhD student. They fell in love. And one night, Vivienne told her the truth. “My secret is that I wish I were a woman.” Norma didn’t run. She listened. Vivienne underwent hormone therapy after conceiving their first child, Baxter, and completed gender confirmation surgery in 2008. They later had a second child, Thalia. Over the next two decades, Vivienne launched six startups, and served as chief scientist at two others. She invented AI systems that could: - Predict manic episodes in bipolar patients - Reunite refugee orphans with surviving relatives - Help autistic children learn to read facial expressions - Manage her son’s diabetes in real-time - Identify and mitigate bias in hiring - Improve cognitive recovery in TBI and dementia patients - Assess student creativity and emotional intelligence In 2011, she co-founded Socos Labs, her fifth company, a “mad science incubator” focused on the intersection of neuroscience, AI, education, and human development. Then she built The Human Trust, a nonprofit data trust that works on complex social challenges: disability, economic exclusion, algorithmic justice… She also co-founded Dionysus Health, where she helped create the world’s first biological test for postpartum depression, using AI and epigenetics to identify risk before symptoms appear. Throughout it all, her central thesis never changed. AI is not the end of the world. It’s not salvation either. It’s a tool, it’s only as useful as the humans who wield it. The real danger, she says, is that we’ll use AI to do just enough. That we’ll automate away our creativity. Flatten our curiosity. Become passive operators of tools we don’t fully understand. When writing her latest book, Robot-Proof, she fed every chapter into Gemini. But not to edit. “I tell it: You’re my nemesis. Tear this apart. Tell me where I’m wrong. Then I run it again: Now you’re a bored reader. Show me where you got lost.” Her work has earned her a spot on the BBC 100 Women list, Inc. Magazine’s 10 Women to Watch in Tech, and more than a dozen research and innovation awards. 💡 Follow Justine Juillard for daily #femalefounder spotlights

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