Introduction: Generative AI is widely considered the fastest-moving technology innovation in history. It has captured the imagination of consumers and enterprises across the globe, spawning incredible innovation and along with it a mutating market ecosystem. Generative AI has also caused a copious amount of FOMO, missteps, and false starts. These are the classic signals of technology disruption – lots of innovation, but also lots of mistakes. It is a like rumpus room with a lot of “kids” going wild. The rumpus room needs adults. Guidance through the generative AI minefield will come from thoughtful organizations who do not panic, who understand the fundamentals of AI, and who manage risk.
Our picks for part 1 of this week’s Adults in the Generative AI Rumpus Room are Google, DynamoFL, AWS
Google Advances Generative AI Search
The News: On August 2, Google provided updates to the Google Search Generative Experience, a new program launched in May. Google Search Generative Experience was set up to enable a limited number of web developers to leverage Google Generative AI capabilities in search. The project started with three AI overview features: 1) step-by step instruction summaries for complex questions, 2) collective tips to specific questions, and 3) important factors to particular buying decisions. The update introduced three enhancements.
Read more details on the Google Search Generative Experience Update on Google’s blog, The Keyword.
Adults because… There has been a great deal of speculation about how generative AI will impact search, but there have not been any significant breakthroughs. When ChatGPT exploded on the marketplace, Google was roundly criticized for its lack of generative AI applications. Was Google asleep at the wheel or does Google know something about generative AI search the rest of us do not know?
Large language models (LLMs) are proving to have issues with accuracy, particularly around hallucinations. They tend to have issues with bias as well. User confidence levels are pretty low, and justifiably so. The monetization model of search return results does not fit into these “just ask a question and get the answer” frameworks, and the search engine players obviously are not excited about losing the search engine revenue stream.
Which means, the reality of generative AI search looks like what Google SGE and Bing are doling out – overviews/summaries tied to link results, but importantly using conversational AI to better understand what users are looking for. Importantly, that includes more two-way communication between the search engine and users to help users get what they are looking for.
Google has the advantage in figuring out what is next in search. Search is the company’s top priority – 57% of Google/Alphabet 2022 revenue came from search. Google dominates search market share. The company has all of the AI experience, expertise, and resources to figure out how to best do next-generation search, including the data to make it work. In a blog post published June 26, Eze Vidra of Remagine Ventures said this:
“Like any tech advancement at scale, to succeed in this endeavor requires deep pockets: cloud resources and costly GPUs, expensive AI engineers, and a working business model, all of which Google already has. But more than anything, it requires a huge amount of data, which is perhaps Google’s biggest competitive moat.”
DynamoFL Introduces Solution Preventing LLMs From Memorizing Private Data
The News: On August 16, DynamoFL announced it raised $15.1 million in Series A funding to expand its product offerings and grow its team to tame LLM flaws.
Adults because… DynamoFL exists because apparently LLMs have a tendency to “memorize” training data and leak it, which would be problematic for companies that would like to leverage their data via an LLM. CEO Vaikkunth Mugunthan told TechCrunch: “Generative AI has brought to the fore new risks, including the ability for LLMs to ‘memorize’ sensitive training data and leak this data to malicious actors. Enterprises have been ill-equipped to address these risks, as properly addressing these LLM vulnerabilities would require recruiting teams of highly specialized privacy machine learning researchers to create a streamlined infrastructure for continuously testing their LLMs against emerging data security vulnerabilities.” The threat is particularly challenging for organizations that are required to meet regulatory and compliance standards.
“While products exist today to redact personally identifiable information from queries sent to LLM services, these don’t meet strict regulatory requirements in sectors like financial services and insurance, where redacted personally identifiable information is commonly re-identified through sophisticated malicious attacks,” he said. “DynamoFL has drawn upon its team’s expertise in AI privacy vulnerabilities to build the most comprehensive solution for enterprises seeking to satisfy regulatory requirements for LLM data security.”
AWS Offers a Generative AI Primer for Executives
The News: On July 21, AWS launched a course called Generative AI for Executives designed to provide a high-level picture of generative AI. In five videos, the course addresses 1) What is generative AI? 2) Why is now the best time to embrace generative AI? 3) Enterprise use cases for generative AI, 4) Training your workforce to use generative AI, and 5) Why is AWS the best place to build with generative AI?
Adults because… Accolades to AWS for addressing a fundamental need in the marketplace: generative AI education. Generative AI has mutated so quickly, many C-suite executives and boards are panicking and have FOMO. The pragmatic solution for that is education. Foundationally, enterprises need to understand what the generative AI ecosystem and stack look like, and then, most importantly, start to explore what problems and challenges they face that generative AI might be able to address.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
Other insights from The Futurum Group:
Google Search Generative Experience: Will Gen AI Impact Search?
Next-Generation Compute: Agents for Amazon Bedrock Complete Tasks
Author Information
Mark comes to The Futurum Group from Omdia’s Artificial Intelligence practice, where his focus was on natural language and AI use cases.
Previously, Mark worked as a consultant and analyst providing custom and syndicated qualitative market analysis with an emphasis on mobile technology and identifying trends and opportunities for companies like Syniverse and ABI Research. He has been cited by international media outlets including CNBC, The Wall Street Journal, Bloomberg Businessweek, and CNET. Based in Tampa, Florida, Mark is a veteran market research analyst with 25 years of experience interpreting technology business and holds a Bachelor of Science from the University of Florida.
