On Real-time AI. Q&A with Madhukar Kumar

Q1. SingleStore Now will take place on October 17, 2023 at the Chase Center in San Francisco. What is the focus of this year’s conference?

• As you’ve probably already guessed, “The Real-Time AI Conference,” will be heavily focusing on real-time AI – the future of real-time generative AI for the enterprise, and hands-on sessions on all things AI, private LLMs, vectors and contextual databases. And of course, SingleStore will also be announcing some major product updates and  presenti live demos on what real-time AI looks like across several industries, as well as sharing some exciting product-related announcements. 

Q2. Why choose Generative artificial intelligence as one of the main topics of the conference?

• Gen AI  has the potential to transform the way we work, and SingleStore is uniquely positioned to be a part of these conversations as data is the key to powering AI applications. Our next-generation, enterprise-grade data platform has built-in vector, multi-model capabilities and some advanced features we are about to announce— putting us at the forefront of the generative AI revolution. 

Q3. What are the potential benefits of Generative artificial intelligence?  

• The potential benefits of generative AI are seemingly limitless. Organizations that unlock this technology are well-positioned to unlock new business models, transform industries, reshape the job market and increase economic productivity. In fact, recent research from Goldman Sachs reveals that generative AI has the potential to make far-reaching changes to the global economy — even driving a 7% increase in global GDP. There’s many more use cases for gen AI across all facets of our daily lives from booking a hotel reservation to finding new movie recommendations, so it’s clear generative AI will be here to stay.  

Q4. What about the risks? 

• From Capitol Hill to people’s living rooms, it seems like everyone is debating the risks behind generative AI. From my perspective, data accuracy and security are major risk factors organizations must consider. Accessing clean and standardized data — especially in real time — enables gen AI applications to deliver accurate and efficient outputs. This also helps minimize potential biases and misinformation as data is free of errors and duplicates. 

Moreover, data security has become even more important as cyberattacks are on the rise. Organizations need to ensure that employees do not put confidential or proprietary information into AI systems. Since AI systems are powered by large language models and data, the information input influences and informs the end output.  

Q5. Do you think that there is going to be one large language model that will dominate the market?

• The world of AI and generative AI is fast evolving. As newer applications, foundational models, supporting technologies and business models continue to saturate the market, some may think that one critical language model will rise to become the overall standard. But I believe that there is not going to be one “universal LLM” that dominates the market — but rather multiple or an ensemble of LLMs or foundational models as organizations start to leverage certain ones that successfully power particular use cases. Truth be told, we have already seen this emerging today in GPT-4, rumored to be not just one massive model but a collection of multiple different models, each with 100 billion parameters all seamed together. 

Q6. How can developers build and scale compelling enterprise-ready Gen AI applications?

• Building and scaling enterprise-ready gen AI applications can easily become not only a complex process, but long-term commitment as they require a multidisciplinary team with expertise in AI, software development, data engineering and domain knowledge. Here are some key steps and considerations for developers looking to undergo this scalability:

Define clear objectives. Like all tasks, start by outlining the specific business objectives and use cases you want your gen AI application to address. By understanding the problem that needs to be solved, your team will be able to do this more efficiently and effectively. 

Data collection and management. Start gathering higher-quality, diverse, representative, and real-time data that is relevant to your use case, as it’s crucial for training precise AI models.

Choose appropriate algorithms and models. Make sure you choose the right machine learning or deep learning algorithms and architectures for your specific application that measure up to your outlined objectives and data. Of course, take the time to experiment with a variety of models, allowing you to see first-hand what fits best for your solution. 

Monitor and debug. How do you ensure your generative AI application is running smoothly? Implement monitoring tools to track the performance of the application, saving time on identifying issues by addressing them in real time. There are new emerging open source tools like LangSmith that can help fast track some of these efforts.

Partnerships and collaborations. Developers and IT teams not only have to ensure current applications are running smoothly for the business, but also continue to build the next generation of its products — meaning, it’s safe to say that their bandwidth is stretched. Consider collaborating with domain experts and other organizations to enhance your gen AI application’s capabilities. 

Q7. Isn’t it too early for this?

• As I mentioned previously, gen AI is here to stay, and data is the central component of its continuous evolution and success. At SingleStore we continue to mature our real-time platform to ensure organizations that utilize gen AI are getting the most up-to-date, accurate data. 

Q8. Does SingleStore database offer AI functions ? Which ones?

• Our database helps power the AI systems of the future. I predict real-time AI will become the next iteration of the AI revolution, and organizations will need a platform that can do split-second curation, consolidate multiple data sources and types quickly, all while providing context to the LLMs instantly. SingleStore is the data plane that sits between AI applications and your data, feeding real-time, curated data and context to power AI systems. We’ll share even more about our AI capabilities during the conference. 

Q9. Will SingleStore announce a number of new product enhancements at the conference? In which areas?

• The short answer? Yes! I won’t spoil the news ahead of the conference, but we will be announcing new SingleStoreDB AI capabilities across three key areas: the core database, intelligence and our ecosystem. 

Q10. Anything else you wish to add?

• We are at the beginning of the next AI evolution as companies, researchers and data scientists are evaluating new capabilities and opportunities for growth. You don’t want to fall behind in this next technological race. Learn more and register for the conference here.

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Madhukar Kumar is the Chief Marketing Officer at SingleStore. 

Sponsored by SingleStore.