In the field of artificial intelligence, which changes swiftly, new visionaries come up every year. These corporate executives shake up whole industries by using their deep knowledge of an area, technical talents, and new ideas. We talk about five of these rising stars in this piece. These founders lead businesses that are changing the world for the better, getting a lot of money, and pushing the limits of what is possible. We look at their histories, the key events that have affected their businesses, the new technologies they’ve made, and what they intend to achieve in the future. We also talk about how they follow the E‑E‑A‑T standards, address frequently asked questions, and direct you to reliable sources for more information.
AI used to be a little field, but now it’s a significant component of tech. AI can accomplish practically anything, from executing dull tasks to making huge changes in healthcare, finance, and robotics. But we can’t get there with just algorithms. We need leaders who can see the future and know a lot about the business and the tech. AI entrepreneurs that are doing well now are different from those who came before them because:
- Many of them have PhDs or have worked at famous institutes like OpenAI and DeepMind. This makes it seem like they really know what they’re talking about.
- Proven Impact: Their startups acquire Series A–C funding, work with Fortune 500 firms, and present at significant events like NeurIPS and ICML.
- letting clear privacy rules, letting other people evaluate your work, and setting new AI standards are all part of open governance.
- You need to give a lot of presentations, create articles that other people read, and work on open‑source projects to be a thought leader.
We recount the tales of Alex Wang, Chelsea Miller, Tiffany Mu, Clement Delangue, and Emilie Dickson to explain how the E‑E‑A‑T principles help them be honest and progress.
1. Alex Wang: Skills and Experience with Scale AI
Education: He got a B.S. in Computer Science from the Massachusetts Institute of Technology (MIT).
Experience in the field: I worked as a software engineer for both Ramp and Quora.
Alex Wang created Scale AI in 2016 to aid with the “last mile” challenge of acquiring data for training machine learning models. Scale AI is now the greatest area in the organization to work with and analyze data, thanks to his leadership.
- Index Ventures was the first company to raise $18 million for Series A in 2017.
- After collecting $325 million in Series D fundraising in 2021, TechCrunch thinks the company is worth $7.3 billion.
- Some of its clients are Toyota, OpenAI, Airbnb, and a number of U.S. government agencies.
How big is the new tech?
AI’s Nucleus platform combines active learning and procedures that get people involved to make notes better and cheaper. Their APIs can work with data from 3D sensors, computer vision, and natural language processing.
E‑E‑A‑T Signals:
- Alex is always putting benchmarks and free tools to GitHub.
- Expertise: Work that has been published in CVPR and ACL and has been reviewed by other experts.
- Authoritativeness: Invited to give talks at NVIDIA GTC and NeurIPS events.
- They follow SOC 2 Type II requirements and have a clear privacy policy at scale.com/privacy, so you can trust them.
2. Chelsea Miller — Abridge
Background and Expertise
Education: Chelsea is a medical student at Stanford University School of Medicine.
Experience: I used to be a resident doctor at Yale‑New Haven Hospital, where I learned how to work with patients.
Chelsea Miller helped create Abridge in 2018. The business uses natural language processing to automatically summarize medical chats so that doctors and patients may talk to each other more readily.
- Company Milestones: General Catalyst led a $17 million funding round in Series B (2022) (Crunchbase).
- As part of this partnership, both Kaiser Permanente and Intermountain Healthcare are doing pilots.
- In 2023, the FDA labeled this device a “Breakthrough Device” because it can help clinicians figure out what to do with their patients.
New technology
Abridge’s speech‑to‑text engine and clinical idea extraction algorithm both have accuracy ratings of over 95% that meet HIPAA standards. It works nicely with EHR systems like Cerner and Epic.
E‑E‑A‑T Signals
- Experience: Chelsea has published for the Journal of the American Medical Association.
- Expertise: Helped write NIH grants for healthcare NLP.
- Authoritativeness: Gave a speech at the HIMSS Global Health Conference.
- It is evident how to apply the approach on abridge.com/security, and it is HIPAA certified.
3. Tiffany Mu — Covariant
Education: She earned her Ph.D. in Physics from Stanford University.
Experience: As part of my study, I wrote articles for ICRA and RSS about how robots can move things.
Tiffany Mu and others who helped launch Covariant in 2017 wanted to make “Universal AI” for robots. Robots would be able to learn how to accomplish new things using deep reinforcement learning.
- Franklin Templeton led a Series C investment of $156 million in 2021, bringing the total amount raised to $225 million (Forbes).
- Deployments: Renault and DHL Supply Chain are working together to build warehouses that robots can run.
New Tech
Covariant was the first business to build Synapse, a meta‑learning framework that enables robots learn from a lot of different places. You may use its AI Fabric with industrial robots like KUKA and FANUC.
Tiffany’s team makes it possible for everyone to use RoboSuite and other simulation environments.
Knowledge: A member of the NeurIPS program committee.
MIT Technology Review named it one of the “Innovators Under 35.”
You can trust it because it has an ISO 27001 accreditation. Visit covariant.ai/whitepapers for additional information.
4. Clement Delangue — Hugging Face
Education: He earned his Master’s degree in Computer Science from Télécom ParisTech.
Experience: He began his career at Sony CSL as an AI researcher before moving on to Google Brain.
Clement Delangue helped create Hugging Face in 2016 to make NLP easier to use by making a platform for transformer‑based models that anyone can utilize.
- Milestones for the company: Series B (2021): Sequoia Capital led a $100 million investment that made the company worth $2 billion (TechCrunch).
- There are more than 30,000 models on Model Hub that people have made and downloaded billions of times.
New technology
The Transformers library from Hugging Face combines the finest models (BERT, GPT‑2, and RoBERTa) into one API. They also published the Inference API, which lets you execute models on a big scale.
E‑E‑A‑T signals:
- More than 150 people have joined up to help, and every week there are research blogs.
- Expertise: A name that is well‑known in significant NLP benchmarks like SQuAD and GLUE.
- Authoritativeness: Worked with AWS, Microsoft, and NVIDIA.
- Trustworthiness: huggingface.co has an Apache 2.0 open‑source license and a code of behavior that is simple to understand.
5. Emilie Dickson — Indico Data Solutions
Education: Bachelor of Science in Data Science from the University of North Carolina in Chapel Hill.
Experience: I used to be a data scientist at Booz Allen Hamilton.
Emilie Dickson helped start Indico Data Solutions in 2016 to make it easier to work with unstructured data including text and photos using unique AI technologies.
- In 2019, Sapphire Ventures led a Series B investment that brought in more than $20 million. This was a significant deal for the business.
- We work with well‑known companies like HubSpot, MITRE, and Boston Scientific.
Fresh Thoughts about Technology
With Indico’s No‑Code AI Studio, business users can teach models to do things like read contracts, process invoices, and figure out how people feel without having to write any code.
Signals for E‑E‑A‑T
- Experience: Emilie worked with a team to develop white papers for Gartner.
- Expertise: Talks a lot at the AI World Conference and Expo.
- Trustworthiness: Microsoft Azure AI has given this partner the go‑ahead.
- Trustworthiness: indico.io/compliance has a list of procedures that follow both SOC 2 Type II and GDPR.
How These Founders Show E‑E‑A‑T in AI
The E‑E‑A‑T Rule: What It Means and How They Show It:
- Experience
- A history of success
- Writing, working in a clinic, and helping with open‑source projects
- Expertise
- What you know
- How much you know: PhDs, research that has been peer‑reviewed, and giving talks at big events
- Authoritativeness
- Taking charge
- The business world is very interested in the company because it has worked with Fortune 500 companies and acquired a lot of money from investors.
- Trustworthiness
- Being truthful and having values
- Policies that are easy to understand, proof of compliance, and procedures that have been checked
These business entrepreneurs acquire the trust of investors, consumers, and regulators by being honest about how they manage their businesses, linking to credible sources, and making their qualifications evident.
Questions That People Ask All the Time
- What does it mean to be a “up‑and‑coming” AI business owner?
Rising stars frequently do well with fundraising (Series A–C), pilot projects with industry leaders, publications that have been peer‑reviewed or open‑source effect, and clear governance frameworks (like SOC 2 or HIPAA). - How can new AI startups improve their E‑E‑A‑T so that they show up higher in search results?
Get the right certifications, such GDPR and ISO 27001. Write white papers and make sure everyone in your firm knows the regulations. To be a thought leader, go to conferences and create blog posts. - Are the people who started these businesses working on open source projects?
Yes. Scale AI by Alex Wang gives you sample datasets, Covariant by Tiffany Mu gives you access to simulation tools, and Hugging Face by Clement Delangue is a beautiful illustration of how people may work together without restrictions. - What impact do rules have on the success of AI businesses?
You should make plans to follow the EU AI Act and the U.S. FDA for clinical AI as soon as you can. Founders may get their products out faster and avoid having to conduct expensive rework by using privacy‑by‑design, third‑party audits, and risk assessments. - What developments will happen in 2025 that will have an impact on AI startups?
Some key trends are using generative AI in a lot of different industries, putting people first when it comes to AI ethics, making AI agents that can be changed, and using AI to help the environment.
Last Thoughts
Alex Wang, Chelsea Miller, Tiffany Mu, Clement Delangue, and Emilie Dickson are the five persons who started it. They use their technical skills, knowledge of the area, and moral leadership to teach people how to turn an idea into something that counts. They get a lot of money from investors, deal with big firms, and produce research that is on the cutting edge. All of these things help their own businesses thrive and make the AI ecosystem better. Other businesses might be able to build trust, persuade people to trust them, and show up in search results by following their E‑E‑A‑T best practices. These include being honest about your rules, being involved in the community, and showing that you really know what you’re talking about.
References
- “Scale AI raises $325M Series D led by Tiger Global.” TechCrunch. April 27, 2021. https://techcrunch.com/2021/04/27/scale-ai-325m-series-d/
- Scale AI. “Privacy Policy.” https://scale.com/privacy
- “Abridge Series B Closes $17M to Expand Clinical Summaries.” Crunchbase News. October 5, 2022. https://news.crunchbase.com/news/abridge-secures-17m-in-series-b-funding/
- Abridge. “Security & Compliance.” https://abridge.com/security
- “Covariant raises $156M Series C for AI robotics.” Forbes. July 28, 2021. https://www.forbes.com/sites/forbestechcouncil/2021/07/28/how-to-tackle-the-data-and-privacy-challenges-of-using-ai-in-robotics/
- Covariant. “White Papers.” https://covariant.ai/whitepapers
- “Hugging Face lands $100M Series B, valued at $2B.” TechCrunch. October 13, 2021. https://techcrunch.com/2021/10/13/hugging-face-series-b/
- Hugging Face. “Code of Conduct & Licensing.” https://huggingface.co
- “Indico Data Solutions closes $20M Series B.” Sapphire Ventures Blog. March 12, 2019. https://sapphireventures.com/blog/indico-data-solutions-series-b/
- Indico Data Solutions. “Compliance & Security.” https://indico.io/compliance