The Gen AI Summit, held at the Palace of Fine Arts in San Francisco last week, gathered top experts and innovators to discuss the future of generative AI. The event featured a jam-packed 3-day agenda of keynotes, panels, workshops, and demos, focusing on the latest advancements and practical applications of AI.
Here are the top ten things I took away from the event:
1. We are entering the next industrial revolution
We are witnessing an era where computing power is not just augmenting but also replacing human brain power at exponential rates. This shift promises to reshape industries and societies profoundly.
2. It’s still early days
Yes, Gen AI adoption is already pretty widespread, but it is important to remember that we are still in the early days of exploration and really understanding what Gen AI will be capable of. Now is the time to start experimenting, as well as starting to develop proactive policies and smart governance to ensure AI develops as a force for good.
3. Everyone is trying to figure out what is going on
There are over 1000 new Gen AI projects created every month. Yes, monthly. You are not alone if you feel totally lost when it comes to developing an AI strategy for your organization's Gen AI strategy. But the consensus is that companies need to get going. Adopting generative AI early enables you to build valuable experience and expertise within your organization and fosters an AI-ready culture and talent pool.
Jeremiah Owyang from Blitzscaling Ventures discusses how to navigate the ever changing AI landscape.
4. It is very expensive to build an LLM
The reason why there are only a handful of tech companies leading the LLM space is the astronomical costs (we’re talking hundreds of millions to billions) to build and train an LLM. And these costs are only expected to go higher, making it harder for new companies to compete with the likes of Open AI and Google.
5. The future is open source
The open-source movement and the democratization of AI was a big topic at the conference. It's based on the idea that the free exchange of knowledge and resources can help drive technological progress, and most importantly open-source models enables businesses to stay competitive without heavy up-front investments, opening up AI innovation to companies of all sizes. Meta’s recent Llama 3 release was a big step toward more open source LLMs, and also a viable competitive threat to Open AI and Google.
6. Enterprises can’t ignore the environmental impact
Training a single Gen-AI model can produce carbon emissions that are almost five times greater than a car's lifetime emissions. Generating one image using AI takes as much energy as fully charging your smartphone. This means integrating Gen AI into the business can be in direct contradiction for companies making net zero carbon pledges. The carbon footprint of any AI platform will need to be evaluated and choosing a method that provides a lower carbon footprint will be a key factor in the choice of a generative AI platform.
The CEO of SambaNova discussed their recent chip advancements that can significantly reduce the amount of computing power needed to run an LLM.
7. It will change how consumers behave
One of the more provocative ideas floated in one of the sessions was a near future in which we won’t need to access the internet, our AI assistants will do it for us. Search volume is already on the decline and is expected to decrease by 25% by 2026. There will be big changes to how we communicate, shop, make plans, book travel and much more.
8. The social impact will be profound
There is a big risk that significant parts of the global population will be left behind when it comes to AI adoption. This was a key topic in several keynotes and panels which highlighted the importance of inclusivity and accessibility, ensuring language diversity and making AI technologies available to underserved communities.
Prof. Johannes Eichstaedt from the Stanford Human-Centered AI group delivered a thought-provoking presentation on the societal implications of AI, including the impact on relationships, politics, and childhood development.
9. AI agents are the new software
As I walked the floor, the one term I noticed in nearly every booth was “AI agent”. AI agents represent a new generation of software, capable of performing complex tasks autonomously. This evolution is set to redefine software development and deployment across various sectors. Workshops highlighted practical implementations and use cases of AI agents across customer service, marketing, personalization and more.
10. Building a strong moat is critical for AI company survival
Proprietary data is crucial for creating a competitive edge. Companies relying solely on public data risk being outcompeted by giants like OpenAI. Accessing and leveraging exclusive data sources is key. Discussions included strategies for securing proprietary data and building robust AI models as well as finding unique business models and distribution channels.
What Does It All Mean for Consumer Brands and What to Do About It?
For consumer brands navigating the Gen AI landscape, these insights underscore the urgency to start experimenting with AI technologies now. It's imperative for companies to begin building their capabilities and forming strategic partnerships to prepare for a future heavily influenced by AI.
Gen AI will not only transform enterprise operations and the nature of work, but it will also forever change consumer behavior. Brands need to prepare for a world where AI agents play a significant role in decision-making, and adapt their strategies to reach and engage consumers effectively.
For tailored strategies and expert guidance, contact us today and let's secure your brand's future in an AI-driven world.
