FT: “Companies in China’s hypercompetitive AI industry at first focused on undercutting each other’s prices for closed-source models. That competition has extended in recent months to open-source models as everyone fights for adoption and public recognition. “Chinese companies often prioritize user stickiness over immediate revenue,” said Charlie Chai, a Shanghai-based tech analyst at 86Research. While startups have a window to attract users, it won’t last long, analysts said, and larger tech companies are often best-positioned to cash in on a big user base by offering related services such as specialized apps or cloud services. “This Darwinian life-or-death struggle will lead to the demise of many of the existing players, but the intense competition breeds strong companies,” wrote Andrew Ng, head of Silicon Valley startup DeepLearning.AI.”
WSJ: “A hybrid approach called neurosymbolic AI is gaining traction with a few companies, notably including Amazon, as developers push AI beyond neural networks’ comfort zone. ChatGPT and other generative AI tools can predict the next word in a sentence astonishingly well, but they can’t always determine whether something is true when there are only limited examples to rely on. And they can deliver even extraordinarily wrong answers with irrational confidence. That can’t be tolerated as models begin to take action on behalf of people or companies…Imandra’s hybrid models combine neural networks with a form of symbolic AI called automated reasoning to serve markets including financial services, autonomous systems and government and defense. Neurosymbolic AI has another advantage, according to Passmore: cost. Unlike pure LLM deployments requiring clusters of expensive graphics processing units, neurosymbolic agents split their workloads. They use GPUs to handle language understanding and standard CPUs to manage complex reasoning and verification.”
Notion CEO Ivan Zhao: “Our sweet spot is more on the things that you need to put in a database. Another way to think about it is like, what is Microsoft Access but for the 2020s, and AI native? Most SaaS is kind of like a relational database, storing some kind of system record of your company, and one workflow on top of that. That’s the part that neither Microsoft nor Google touches today. There are spreadsheets, but there are not many database use cases. We want to consolidate and commoditize that, and give people the LEGO of those database use cases, such as project management and ticket tracking. Some companies use them for CRM, or managing application trackers. For reporters, you can manage all your leads and the stories. Those are database use cases…If you think about what’s happening in software right now, software is largely people providing the tools for humans to use, and more and more companies are realizing, “Wait a second, we have this new thing called a language model. It’s like a human mini-intern in a box, and we should design our software to teach AI how to use it so humans can ask AI to do the work and use the tools, and humans can do way more things with it.””
PwC on igniting growth: “Ignite innovation everywhere. Start by examining your business, operating and energy models, as these areas are the most likely to require big changes. As industry boundaries blur, smart companies will seek out new ways to transform how they create, deliver and capture value. Master the right sources of advantage. As you chase new growth opportunities, which foundational sources of advantage will you rely on, and how robust are they? Turn obstacles into enablers. Last, competing in the coming decade will require transforming today’s obstacles into enablers of growth. Common blockers include slow decision-making, poor resource allocation and insufficient capabilities needed to succeed as part of an ecosystem.”
