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Jaclyn Rice Nelson is co-founder and CEO of Tribe AI, helping organizations drive change with machine learning by building new avenues to attract the best talent in tech.
Before launching Tribe AI, Jaclyn spent most of his career at Google partnering with enterprise companies and developing new products. She was an early employee at CapitalG, Alphabet’s growth investment firm, where she built a network of 50,000 professionals and helped grow-stage technology companies like Airbnb to develop their technology infrastructure. Advised on scaling, data security and leveraging machine learning for growth.
You were the business lead for Google Helpouts. Google Helpouts was a marketplace that connected people to experts via live video and operated autonomously within Google. He then served as Vice President of Growth at CapitalG, a fund that invests in growth stage companies. How did this experience shape your view of building an AI talent agency?
I worked at Google for nearly eight years, but it wasn’t until about three years into the company that I started working directly with engineers. I joined Helpouts as one of his first business his person. The experience of having 30+ engineers sitting in the same room was a completely different (and much quieter) experience than on the sales floor. This gave us a firsthand view of the product and engineering and allowed us to share customer feedback directly. This was also our first experience building a marketplace for sharing expertise. This is a theme that has carried over throughout my career and led to the start of Tribe AI.
Startups within big companies are doomed to fail, and Helpouts are doomed to fail. Even though he expanded the global launch and team headcount to 150 people. I moved into a late-stage venture fund, CapitalG (previously known as Google Capital), to help build a similar expert network of Google specialists that is only accessible to the companies we invest in. bottom. -Stage companies such as Airbnb and Stripe have found it very difficult to adopt data science and machine learning. We were the first line of defense to their questions and wondered what a company would do without their go-to Google.
I saw the value of data and machine learning at Google and a great opportunity to understand the value of AI, giving companies access to underutilized talent in Silicon Valley and beyond. . And so I became an entrepreneur and Tribe AI was born.
What are some of the dramatic wealth creation opportunities currently being seen in AI?
AI is the next gold rush. Advances in generative AI create an urgency and means for every company to become an AI company. There is a great opportunity for start-ups to build huge businesses and large incumbents to become AI companies. This means many opportunities to build amazing products that solve real problems, serve millions of people, and generate enormous wealth for founders, investors, and executives in the process. increase.
You became a co-founder of Coalition Operators in 2021. What specifically do you look for in founders who invest?
Since I left CapitalG in 2018, I have been an active investor, eventually launching a fund called Coalition Operators with three outstanding founders and operators. As founders, we rely on what we each know best. So, I invest a lot in data, AI, ML, and B2B SaaS. We primarily invest in seed-stage companies, so we optimize founders above all else. I’m looking for someone who is passionate, has unique insight into their target market, and is a little crazy (in a good way).
Can you tell us the origin story behind Tribe AI?
I met co-founder Noah Gale while at South Park Commons, a tech community in San Francisco. We were surrounded by top ML engineers who left big companies for freedom. They no longer wanted to climb the corporate ladder or spend all their time optimizing ads. They wanted to start their own company, work on their own research, and gain experience solving industry-wide problems.
Opportunity revealed. We give our top tech talent the freedom to work on the flexible and unique projects they really want to work on, and provide a strong community of other talented engineers who connect on the basis of mutual benefit. In doing so, we created an infrastructure to ensure that the best people do only what they are good at and never do anything they are not good at.
We’ve built a curated network of top AI specialists to help companies apply machine learning to their businesses while giving them the freedom they want. We work not only with start-ups, but also with PE firms, enterprise companies, etc. Every company needs to be an AI company, and Tribe is helping make that vision a reality.
Why are companies of all sizes struggling to hire machine learning talent?
First of all, it’s very difficult to measure technical talent as a business leader. Understanding exactly what skills you need and how to approach a data problem can be difficult unless you have strong technical acumen or direct machine learning experience.
Another reason is rarity. As AI models like ChatGPT become more mainstream, all companies are trying to find ways to incorporate generative AI into their business. Competition for top talent is fierce, many of which have been captured by some of the leading AI companies.
How will Tribe AI solve this employment dilemma?
We built the Tribe to give the best tech talent new career paths that combine freedom, reward and interesting work. Clearly, this is attractive to many talents. We receive dozens of applications a day and accept small shares. By pooling this talent into our network, we can deploy it to projects that fit your skills and schedule. For some, this means consulting her 40+ hours a week, while others want to take on an advisory role while starting their own company.
Clearly, this approach has huge benefits for businesses as well. The reality is that most companies don’t need a full-time ML team. Often what they need is a few specialists to build the early stages of a technical roadmap or proof of concept, and then a full stack engineer or front end to maintain or scale what they have built. End engineer. This gives companies access to top talent and the flexibility to work in ways that foster both innovation and success.
The Tribe receives dozens of applicants a week, how do you vette talent?
First, we screen applicants for their qualifications and technical expertise. If they meet the criteria, we set up interviews to further explore their experience, communication skills, and problem-solving abilities. All interviews are conducted by her C-level machine learning talents to ensure that she is confident in the abilities of those accepted into the Tribe network. This is important because top engineers want to be around other top engineers. The network effect of this business for both customers and talent is huge so it all comes down to getting the best talent in the market . We have ML engineers who have done research at companies like OpenAI, AI founders with multiple outlets, people who have led teams at major technology companies, and everything in between. Our goal is to build a magnet for this talent, and companies follow from there.
What value do companies see in Tribe AI’s network in addition to, or possibly instead of, having a full-time AI team in-house?
First and foremost, Tribe AI gives companies access to top AI talent from companies like Google, Apple, Amazon, and Nasa. The reality is that most companies, unless they are top-tier AI labs or tech giants, can’t hire such talent. So for many companies, working with Tribe is the only way to access this great AI talent.
Another factor is flexibility. Hiring a full-time team takes time and very specific skills before he really understands what it takes to get him working on set. We work with many companies who send Tribe experts to augment their in-house teams for specific projects. We also work with companies looking to accelerate their velocity while considering hiring with a small pool of talent, or those who need help identifying the best use cases for AI.
The final piece is our experience. We are really making strides when it comes to AI. We use a unique matching system built on GPT-3 that allows us to quickly find the exact right person for every engagement. We have built an infrastructure that allows us to enter and make an impact.
How will project-based work change the way companies incorporate AI into their business?
We believe project-based work is the future of AI/ML. Project-based work will dramatically change how companies use AI. This is because technical talent can be used to meet very specific needs rather than meeting the general requirements of a more universal role. This model helps identify exact talent gaps to inform the types of AI/ML professionals needed.
This is the way top talent wants to work, and it’s more profitable for companies. Until now, only the world’s largest companies had access to top ML talent. These companies still struggle with slow, difficult and costly hiring efforts. This all-new model enables companies of all sizes to accelerate ML adoption and see results faster in ways not possible with traditional hiring practices.
Thanks for the great interview. Readers interested in learning more or looking to hire can visit Tribe AI.
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