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Understanding the regulatory landscape in AI governance is essential for organizations to comply with emerging regulations, such as the EU AI Act. Responsible AI goes beyond principles to accountability, requiring organizations to demonstrate ethical practices in their AI implementations. Model transparency ratings provide a valuable tool for evaluating large language models and assessing their risk factors based on public disclosure.
In this episode we sit with Gerald Kierce, co-founder and CEO of Trustible AI, a leading technology provider focused on responsible AI governance. Gerald provides insights into his background, including his experience at FiscalNote and his vision for Trustible AI. The discussion covers how Trustible AI helps organizations manage AI risks, comply with emerging regulations, and implement responsible AI practices. Gerald also shares his thoughts on the regulatory landscape, the role of third-party audits, and the challenges and strategies in building an AI governance platform. The conversation also touches upon Trustible AI's recent feature, the model transparency ratings, and the complexities of fundraising in the AI sector.
If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.
Founder Bio:
Gerald Kierce is the Co-Founder & CEO of Trustible – a leading technology provider of responsible AI governance. Its software platform enables AI and compliance teams to scale their AI Governance programs to help build trust, manage risk, and comply with AI regulations. Prior to founding Trustible, Gerald was an executive at FiscalNote (NYSE: NOTE) where he spent nearly a decade at the company across a variety of roles including VP & General Manager of their AI Solutions division, Corporate Development, Chief of Staff, Product Marketing, and Customer Success. FiscalNote was the most recent DC-based company to go public in the New York Stock Exchange in August of 2022. He is originally from San Juan, Puerto Rico.
Time Stamps:
01:46 Gerald's background and journey into AI
03:58 Navigating AI without a technical background
07:45 Trustible AI pain point: AI Governance and Compliance
13:36 Managing AI risks and mitigation strategies
17:13 The shift from responsible AI to accountable AI
21:34 Navigating AI governance and regulatory compliance challenges
25:50 AI in practice: Real-world applications
28:25 Challenges and solutions in deploying generative AI models
30:04 Building an AI startup: From vision to product adoption
36:31 Understanding model transparency ratings for evaluating AI risks
41:14 Fundraising and market dynamics in AI
45:23 Future Directions and how to get in contact with the Trustible team
Resources
Company website: https://www.trustible.ai/
LinkedIn: https://www.linkedin.com/company/trustible/
Twitter: https://twitter.com/TrustibleAI
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In this episode, we sit with Omar Tabba, Chief Product Officer at Brainbox AI, to delve into the transformative use of artificial intelligence in building automation and energy efficiency. With over 20 years of experience, Omar shares his journey into the AI sector, real-world applications of AI in managing HVAC systems, and Brainbox AI's innovations like ARIA, the world's first virtual building assistant.
We discuss the operational and environmental benefits of AI in smart building management, including significant reductions in energy consumption and carbon emissions. The conversation highlights the importance of normalized data, the role of AI in predictive maintenance, and the cultural and technical synergies needed to drive AI innovations in the built environment.
If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.
Founder Bio:
Omar Tabba leads the product management function at BrainBox AI. With more than 20 years of expertise in energy efficiency, artificial intelligence, and building automation, he has held various positions spanning technical, sales, and executive roles. Prior to joining BrainBox AI, he led the digital solutions team at the General Electric Current business unit, where he supported the sale of Current’s digital solutions to Fortune 200 companies as well as the product, marketing and business development functions. Earlier in his career, Omar co-founded a venture-backed lighting control company and spearheaded sales for Distech Controls (NYSE:AYI) across Eastern North America and the Middle East.
A patent holder, Omar has applied building automation and energy management systems globally across multiple vertical markets (e.g., retail, commercial office, education) and in portfolios ranging from single buildings to several thousand.
Time Stamps:
01:55 Omar's journey into AI and smart buildings
05:11 Pain point that Brainbox is solving: building automation systems
09:01 ROI benefit examples
11:37 The role of AI in building management
16:05 AI applications in building maintenance
20:40 Acquiring and integrating building data
22:17 Solving data retention issues
23:54 Introducing ARIA: The Virtual building assistant
26:28 Building a specialized technical team
30:00 Navigating the AI talent market
32:25 The importance of cultural fit for hiring the right team
36:05 Funding journey and investor insights
41:00 The future of AI in building management
43:10 Exciting Announcements for 2024
Resources
Company website: https://brainboxai.com/en/
Instagram: https://www.instagram.com/brainboxai/
LinkedIn: https://www.linkedin.com/company/brainboxai/
Facebook: https://www.facebook.com/BrainBoxAI
Twitter: https://x.com/brainboxai
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In today’s episode, we sit with Patricia Thaine, the Co-founder and CEO of Private AI. Patricia shares her journey into the world of AI, the challenges companies face in adhering to data protection regulations like GDPR, and the vital role of privacy-enhancing technologies. She elaborates on how Private AI leverages artificial intelligence to help companies identify and safeguard personal information within their data, ensuring compliance and protecting customer privacy. Additionally, Patricia emphasizes the importance of data minimization and discusses the real-world applications of AI in addressing privacy and data protection challenges.
Private AI is addressing the pain point of data privacy by leveraging AI to help companies identify and protect personal information in unstructured data. Patricia explained that AI is crucial in understanding the context of the data and making accurate predictions about what constitutes personal information. While traditional methods like regular expressions can be used, they often fall short due to their inability to handle the complexity and variety of unstructured data.
If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.
Founder Bio:
Patricia Thaine is the Co-Founder & CEO of Private AI, a Microsoft-backed startup who raised their Series A led by the BDC in November 2022. Private AI was named a 2023 Technology Pioneer by the World Economic Forum and a Gartner Cool Vendor. She is also a Computer Science PhD Candidate at the University of Toronto (on leave) and a Vector Institute alumna. Her R&D work is focused on privacy-preserving natural language processing, with a focus on applied cryptography and re-identification risk. She also does research on computational methods for lost language decipherment. Patricia is a recipient of the NSERC Postgraduate Scholarship, the RBC Graduate Fellowship, the Beatrice “Trixie” Worsley Graduate Scholarship in Computer Science, and the Ontario Graduate Scholarship. She is the co-inventor of one U.S. patent and has ten years of research and software development experience, including at the McGill Language Development Lab, the University of Toronto’s Computational Linguistics Lab, the University of Toronto’s Department of Linguistics, and the Public Health Agency of Canada.
Time Stamps:
02:10 Patricia's background and journey into AI
03:54 Challenges and solutions in data privacy
06:15 Consequences of noncompliance in data protection
09:43 Enhancing data privacy in AI startups
11:34 Unraveling data privacy in AI for multinational compliance
15:11 Demystifying AI’s role in data analysis and application
17:10 AI, privacy, and internal risks in large language models
21:09 Building the private AI platform: Team and technology insights
23:35 Efficiency and expertise in building custom machine learning models
28:33 Catalysts and compliance in conversational AI adoption
30:35 Evaluating AI’s role over regular expressions in customer solutions
33:07 Investing millions for superior Data-Driven AI models
34:51 Fundraising journey for an AI startup
38:20 Private AI upcoming announcements and where to find them
Resources
Company website: https://private-ai.com/
Youtube: https://www.youtube.com/@privateai715
LinkedIn: https://www.linkedin.com/company/private-ai/
Patricia’s LinkedIn: https://www.linkedin.com/in/patricia-thaine/
Twitter: https://twitter.com/_PrivateAI
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Artificial intelligence (AI) has come a long way since its early days of identifying cats in images. Today, AI is transforming the way we work and interact with technology, thanks to the development of AI agents. These agents, powered by advanced AI models, act as virtual colleagues, capable of automating tasks, providing insights, and orchestrating complex workflows
In this episode we speak with Alexander de RidderDirector, co-founder and CTO of Ink Co. The conversation explores Alexander's journey in the AI and machine learning space, starting from early innovations in computer vision to the development of Smith OS, an operating system for collaborative AI agents. Alexander shares insights into the transformative potential of AI in marketing, SEO, and business, highlighting his contributions through patenting semantic optimization technology and predicting Google rankings with impressive accuracy. The discussion also covers the impact of AI on consumer and enterprise levels, the advent of AI agents and multi-agent systems as future workforces, and the challenges and opportunities presented by AI integration into various sectors. Alexander emphasizes the importance of AI orchestration through tools like Smith OS and offers advice for individuals interested in AI, highlighting AI technology's democratizing potential.If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.
Founder Bio:
Alexander De Ridder is an entrepreneur, technologist, and visionary focused on leveraging AI to transform marketing and business. As Co-Founder and CTO of INK Content, Inc., he currently leads the development of Smyth OS, an operating system for collaborative AI agents.A recognized thought leader on the future of AI, Alexander paints a bold vision for how AI assistants will interact with specialized websites to deliver hyper-relevant, personalized experiences he calls "Web 3.0." He sees major changes on the horizon as AI transforms search, e-commerce, and human-computer interaction.With deep expertise in areas including AI, machine learning, marketing, and SEO, Alexander frequently shares his insights on where technology is heading and how businesses can prepare. He advises enterprises on transitioning to AI-driven strategies and workflows.
Time Stamps:
02:00 Alexander's journey: from machine learning to AI pioneering
05:26 The evolution of AI in search and content marketing
08:03 Revolutionizing content creation with AI
13:08 The future of AI agents and workforce automation
19:24 The exponential growth of AI through multi-agent systems
23:17 Consumer domination and workspace revolution
28:35 Exploring the capabilities of AI in automation
30:32 Showcasing SmythOS: practical applications and examples
35:22 Building your Own AI agent: Accessibility and Skill Levels
41:46 The Technical Backbone of SmythOS
47:30 SmythOS found raising journey: the future of work with AI agents
51:54 How to get in contact with the SmythOs team
Resources:
Company website: https://smythos.com/
Facebook: https://www.facebook.com/people/SmythOS/61552328188105/
LinkedIn: https://www.linkedin.com/company/smythos/
Twitter: https://x.com/adridder
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In this episode, we sit with Brian Rue, the CEO and co-founder of Rollbar. They discuss Rollbar’s continuous code improvement platform, which uses AI to help developers proactively discover, predict, and fix errors in their code. Brian shares his background in coding and how his experience in building social games on Facebook led him to start Rollbar. He explains the evolution of their error monitoring solution and how they incorporated AI to provide accurate alerts and signals to developers. They also discuss the impact of AI on developer productivity and the value proposition of Rollbar’s AI-driven solution.
The introduction of AI into Rollbar’s error monitoring solution revolutionized the process. By leveraging AI, Rollbar could accurately identify and group errors, saving developers from sifting through millions of error reports. The AI solution incorporated domain-specific knowledge and inferred patterns based on data, enabling developers to focus on the most critical issues. This automation not only improved the accuracy of error detection but also allowed developers to respond faster to issues, leading to increased efficiency and productivity.
If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.
Founder Bio:
Brian is the CEO and Co-founder of Rollbar, the leading continuous code improvement platform that proactively discovers, predicts, and remediates errors with real-time AI-assisted workflows. With Rollbar, developers continually improve their code and constantly innovate rather than spending time monitoring, investigating, and debugging. Brian founded the company with Cory Virok in 2012. Prior to Rollbar, Brian was the CTO and Co-founder of Lolapps, a leading publisher of independent games on social networks and mobile platforms. Brian attended Stanford University where he studied Management Science and Engineering.
Time Stamps:
01:38 Brian Rue background and professional journey
05:20 Enhancing error monitoring through AI integration
09:26 Maximizing developer efficiency through AI automation
13:33 Acquiring talent and technology for AI integration
16:40 Managing Time Zones in Global Teams
19:27 Rollbar's go to market strategy
21:47 Balancing product adoption and value proposition in sales
24:13 Navigating VC funding in a challenging tech ecosystem
25:46 What's coming up for Rollbar in 2024, and what are the future plans
Resources
Twitter: https://x.com/rollbar
Company website: https://rollbar.com/
LinkedIn: https://www.linkedin.com/company/rollbar/ -
In this episode we speak with Wendy Gonzalez, CEO of Sama, a company at the forefront of providing high-quality training data for AI technologies, used by major companies like Walmart, Google, Nvidia, GM, and more. Under Wendy's leadership, Sama has gained recognition for its rapid growth and her dedication to creating employment opportunities in underserved communities. The conversation delves into Sama's foundation on the belief of distributing opportunity through job creation in the digital economy, their focus on AI data pipeline development, and the shift towards data annotation and AI model training. Wendy discusses the importance of human judgment in AI development and Sama's approach to employment, and fostering a diverse and skilled workforce. She also touches on Sama's involvement with synthetic data, the ethical considerations in AI, the potential of generative AI in various applications, and how Sama addresses the challenges and opportunities in AI technology development while emphasizing social responsibility and workforce development in underrepresented communities.
If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.
Founder Bio:
Wendy Gonzalez is the CEO of Sama, which is a leader in providing high-quality training data to power AI technology and is used by leading technology companies such as Walmart, Google, NVIDIA, GM, and Getty. Under Wendy’s leadership, Sama has placed on the Inc. 5000 list as one of America's fastest-growing private companies for the past four years. She has also been recognized by the Globee Awards for Women in Business, the TITAN Awards for Women in Business, and the Stevie Awards for Women in Business due to her leadership and Sama’s growth.
Prior to taking on the role of CEO, Wendy spent five years at Sama as COO, and is an active Board Member of the Leila Janah Foundation. As CEO, she is one of few female leaders within the male-dominated AI industry. With two decades of managerial and technology leadership experience, Wendy is an executive passionate about building high-performing, high-functioning teams that develop and scale innovative, impactful technology.
Time Stamps:
02:14 Wendy's Journey: from management consulting to AI leadership
04:03 Bridging talent and opportunity in AI
06:42 From data annotation to AI model validation
08:24 Sama's approach to AI data
13:05 How Sama works with businesses
14:27 Generative AI vs traditional ML
21:08 Sama's Role in the future of AI
23:38 Monetization and investment in AI technologies
25:49 The importance of high accuracy in AI applications
28:01 Addressing multilingual support and complex data categories
29:52 Data privacy and security in AI development
36:06 The role of synthetic data in enhancing AI models
37:58 Empowering underrepresented communities through AI jobs
43:37 Excitement and challenges in AI for 2024
Resources
Company website: https://www.sama.com/
Twitter: https://twitter.com/SamaAI
Instagram: https://www.instagram.com/sama_ai_/
LinkedIn: https://www.linkedin.com/company/sama-ai/ -
Data quality issues can arise at various stages of the data pipeline, from data ingestion to model deployment. Common issues include null values, schema drift, and incorrect calculations. These seemingly small issues can have a significant impact on the accuracy and reliability of the data, leading to broken dashboards and loss of trust in the data system.
In this episode, host Darius Gant interviews Abe Gong, the founder and CEO of Great Expectations, a leading data quality tool. Abe shares his insights into the world of data quality and how Great Expectations is solving the systemic problem of data quality in organizations. He explains the importance of building a robust testing system for data, similar to what software engineers do, in order to ensure accurate and reliable data. Abe discusses common data quality issues and how Great Expectations helps teams identify and fix these issues. He also explores the intersection of data quality and AI, highlighting the role of GX in ensuring the accuracy and trustworthiness of AI models. Throughout the conversation, Abe emphasizes the need for collaboration and communication in data teams to build trust and achieve data-driven success.
If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.
Founder Bio:
Abe Gong is a founder and CEO at Great Expectations, the world’s leading open source tool for data quality. Prior to working on Great Expectations, Abe was Chief Data Officer at Aspire Health, the founding member of the Jawbone data science team, and lead data scientist at Massive Health. Abe has been leading teams using data and technology to solve problems in health, tech, and public policy for over a decade. He speaks and writes regularly on data, AI and entrepreneurship.
Time Stamps:
01:58 Abe Gong’s background and experience in data science
03:45 The pain point in the market that led to the creation of great expectations
05:00 Common errors and issues in data quality
06:47 Identifying and solving data quality issues
09:43 How great expectations support companies deploying AI models
12:45 Great Expectations involvement in generative AI use cases
16:34 Understanding the sensibilities and workflows of data developers
19:42 Building a remote-first team with a focus on open-source collaboration
22:11 Tips for running a remote team efficiently and effectively
24:41 Hiring independent and action-oriented individuals for remote work
27:24 Raising founds journey for Great Expectations.
30:08 Importance of technical leads on data teams
32:52 Difference between enterprise software sales and open source models
34:06 What is coming up for Great Expectations in the 2024
Resources
Company website: https://greatexpectations.io/
Twitter: https://twitter.com/expectgreatdata
LinkedIn: https://www.linkedin.com/company/greatexpectations-data/ -
One of the primary benefits of AI in cybersecurity is its ability to enhance perception and reasoning. Traditional security measures often rely on manual analysis of logs and data, which can be time-consuming and prone to human error. AI, on the other hand, can analyze vast amounts of data in real-time, detecting patterns and anomalies that may indicate malicious activity. This improved perception allows for early detection of threats and faster response times.
In this episode, we speak with Gregor Stewart, an executive at Sentinel One, about the intersection of AI and cybersecurity. Gregor shares his journey in the tech industry, from his early fascination with text adventure games to his academic studies in AI and cognitive science. He discusses the evolution of natural language processing (NLP) and how AI has transformed the field of cybersecurity. He also explains how Sentinel One uses AI to detect and mitigate malicious activity on endpoints and in cloud environments emphasizing the importance of automation and autonomy in cybersecurity and how AI can enhance the speed and accuracy of threat detection and response.
If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.
Founder Bio:
Gregor Stewart is Tech executive with over 20 years of experience in software development (engineering and product management) at both privately and publicly held companies. Deep domain expertise in delivering Data Science, Machine learning and AI applications, with a particular focus on Natural Language technologies, Generative AI models (including fine-tuning, cost optimization) and multi-modal, conversational problems like customer journey modeling. Led and scaled engineering and research teams across the world through IPO (NYSE:MDLA) and private equity aquisition (Thoma Bravo), both organically and by acquisition; Adept at building and scaling large, high-performing distributed teams that successfully deliver products to enterprise and mid-market customers.
Time Stamps:
02:20 Introduction and background of Gregor Stewart
10:12 Balancing expectations as a person guiding AI development
12:37 Executive challenge of prioritizing and budgeting AI projects
14:05 Overview of Sentinel One’s core products and implementation of AI.
16:46 The complexity of maintaining a good security posture
19:58 The skill level required for resolving security issues with AI assistance
21:53 AI’s ability to detect and resolve attacks that non-AI systems can’t.
28:09 How AI allows for more efficient querying of security data.
31:37 Transitioning from a startup to a larger organization with centralizing AI expertise.
36:18 Using AI to distribute and answer information
38:13 What is coming up for Sentinel One in the 2024
Resources
Company website: https://www.sentinelone.com/
Instagram: https://www.instagram.com/sentinelsec/?hl=es
Twitter: https://twitter.com/SentinelOne
LinkedIn: https://www.linkedin.com/company/sentinelone/ -
In a world driven by data, organizations are constantly seeking ways to collaborate and leverage the power of artificial intelligence (AI) to solve complex problems. However, the challenge lies in the fact that data collaboration often requires sharing sensitive information, which raises concerns around privacy, security, and intellectual property (IP) protection.
In this episode we interview Alon Kaufman, the CEO of Duality Technologies, about the challenges and solutions surrounding data collaboration in the age of AI. Alon shares his journey in the field of AI, starting from his early days in computational neuroscience to his experience at RSA and ZoomInfo. He explains the problem of data collaboration and the need for secure methods to share data while maintaining privacy and security.
Alon introduces Duality Technologies and its mission to unlock the potential of data collaboration through encryption and privacy-enhancing technologies. He discusses the unique approach of using mathematics and encryption to enable secure data collaboration, highlighting the benefits for industries such as healthcare, finance, and government.
If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.
Founder Bio:
Alon Kaufman, Co-Founder and CEO of Duality Technologies, has 20 years of experience in the hi-tech arena, commercializing data-science technologies, leading industrial research and corporate innovation teams. Prior to founding Duality he served as RSA’s global director of Data Science, Research and Innovation. In addition to his leadership experience, he is accomplished in the fields of artificial intelligence, machine learning and how they interplay with security and privacy, with over 30 approved US patents in these fields. He holds a PhD. in Computational Neuroscience and machine learning from the Hebrew University and an MBA from Tel Aviv University.
Time Stamps:
01:40 Alon’s background and transition into AI
04:52 Alon’s experience in data science and problem-solving
07:37 The challenge of data collaboration within AI
10:22 Duality as a software solution for data collaboration
13:34 Encrypted collaboration without sharing data
17:54 AI’s role in accessing unbiased data
20:33 Using duality to access partner’s data
23:50 Duality as a try-before-buy platform for startups
26:25 Government collaboration for cross-border use cases
29:06 The technical talent required in the early phases of building Duality
32:06 Building a global team and leveraging expertise in different locations
34:32 Balancing remote work and in-office collaboration for productivity
38:46 The funding journey and the benefits of being part of the AI ecosystem.
40:04 What is coming up for Duality in the 2024
Resources:
Company website: https://dualitytech.com/
Twitter: https://twitter.com/DualityTech
LinkedIn: https://www.linkedin.com/company/duality-technologies/
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Generative AI, particularly retrieval augmented generation (RAG), is in high demand as companies seek to leverage its capabilities to improve operational efficiency and enhance customer experiences. - Building a successful generative AI project requires a combination of engineering and research skills, as well as a deep understanding of the specific use case and data sources involved. - Ongoing maintenance and monitoring are crucial for ensuring the continued success of generative AI projects, as models need to be regularly updated and evaluated to maintain accuracy and relevance.
Today we sit with Bartek Roszak, who is the head of AI at STXNext, about the integration of ethical AI practices and compliance. Bartek shares his journey in AI, starting as a stock trader and transitioning to data science and deep learning. He discusses the evolution of STXNext from a Python development house to an AI-powered company and the growing demand for generative AI solutions. Bartek explains the concept of retrieval augmented generation (RAG) and its applications in various industries. He also highlights the importance of prompt engineering and the challenges of maintaining AI models post-deployment.
If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.
Founder Bio:
Bartek Roszak is a luminary in the AI sphere and the driving force behind STXNext’s AI strategy. With significant roles and achievements in the field of AI, Bartek has a background in stock trading and transitioned to data science and deep learning. He has experience in building AI solutions for various industries and specializes in generative AI, particularly in the area of retrieval augmented generation (RAG). Bartek is passionate about integrating AI into business operations and helping companies leverage AI for competitive advantage.
Time Stamps:
02:26 Bartek’s background and transition into AI
04:51 Evolution of STXnext into an AI-focused company
07:12 Popular AI use cases and interest in generative AI
10:07 What is retrieval augmented generation (RAG): Use cases and interest
12:51 External uses of generative AI with high demand
14:48 Skills required to build and deploy gen AI products
16:38 Minimum experience with LLMs or machine learning needed to work with Gen AI
19:49 The importance of quality assurance in machine learning projects
21:43 Importance of having skillsets in prompt engineering.
23:19 Diversifying LLM base to mitigate downtime risks
24:52 Creating a competitive advantage by using LLM as part of a larger system
28:04 The process of working with clients on AI use cases
32:51 Post-project maintenance and client involvement
34:23 Transitioning the project to the client’s data science team
36:40 STX Next’s plans for 2024Resources
Company website: https://www.stxnext.com/
Twitter: https://twitter.com/STXNext
LinkedIn: https://www.linkedin.com/company/stx-next-ai-solutions/
Instagram: https://www.instagram.com/stx_next/ -
Generative AI has become a game-changer in various industries, with applications ranging from content generation to market research. - The demand for generative AI talent is high, and it is an employee’s market in this field. - Prompt engineering is crucial in effectively communicating with language models and ensuring accurate and human-like outputs.
Building Gen AI products requires a different skill set compared to traditional software development. It’s important to understand prompt engineering, have knowledge of neural networks and backpropagation, and be familiar with frameworks like Langchain and vector databases.
In this episode, we interview Ehmad Zubair, the co-founder of a web and mobile development agency that has recently shifted its focus to generative AI. Ehmad shares his journey from being a software engineer to diving headfirst into the world of AI. He discusses the challenges of building real-world AI applications and the skill sets required for success in the field. Ehmad also highlights the exciting use cases his company is working on, including AI-powered content generation and market research tools. Don’t miss this insightful conversation about the booming world of Gen AI.
If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.
Founder Bio:
Ehmad Zubair is the visionary CEO of Cogent Labs, a cutting-edge software development agency he founded in 2021. With a robust foundation in software engineering since 2014, Ehmad has steered Cogent Labs from its inception to a dynamic team of 52 professionals in just three years. Under his leadership, the company has carved out a niche in Generative AI, alongside web and mobile development, contributing to global impact projects, including collaborations with UNICEF's Internet of Good Things.
Ehmad is not just a business leader but also an influential voice in the tech community, running a successful YouTube channel. Here, he shares insights into the software engineering landscape in Pakistan, offering valuable knowledge to aspiring engineers and industry veterans alike.
Outside of his professional pursuits, Ehmad is an avid football enthusiast and a content creator, further showcasing his diverse interests and talents. Follow his journey and insights on his website, cogentlabs.co, on Instagram @ehmad.zubair, and on his YouTube channel, Ehmad Zubair, to stay at the forefront of software engineering and Generative AI innovations.
Time Stamps:
02:09 Introduction and background of Ehmad Zubair
04:06 The rise of online programs like Udacity for AI upskilling
07:46 Entry into building real-world AI applications
09:48 Use cases and applications of generative AI
14:48 Challenges of selling Gen AI to enterprise customers due to data privacy and security concerns
18:05 Challenges of working with cutting-edge generative AI models
21:04 Importance of hiring curious and adaptable team members
22:00 Required skills for building generative AI products
25:56 Prompt engineering as a programming language for generative AI
27:58 Code is still the most efficient way to program machines.
29:41 Finding the right talent for Gen AI
32:28 Building tools to save time and money is the focus.
34:54 Upcoming Projects for this 2024.
37:30 Introduction to a fact-checking AI agent that helps minimize hallucinations and hyperboles
40:11 How to get in contact with the Cogen Labs team
Resources
Company website: https://cogentlabs.co/
Facebook: https://www.facebook.com/cogent.labs.co
LinkedIn:https://www.linkedin.com/company/cogentlabs/
Instagram: https://www.instagram.com/cogent.labs.co/
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In today’s fast-paced business environment, time is a valuable resource. Yet, many employees find themselves bogged down by mundane tasks that hinder their ability to focus on more strategic work. Xembly, an AI-powered platform, seeks to address this challenge by automating group tasks and streamlining collaboration processes.
In this episode, we interview Jason Flaks, co-founder of Xembly, about the role of AI in automating mundane tasks for knowledge workers. Jason shares his nontraditional path into the world of AI, starting as a musician and transitioning to software engineering. He discusses the pain points Xembly aims to solve, such as group collaboration tasks like scheduling meetings and taking meeting notes. Jason explains the special sauce of AI in solving these problems more efficiently and highlights the differentiation of Xembly from other tools in the market. He also dives into the various AI components involved in Xembly’s solution, including conversational understanding, planning, negotiation, and distribution of information.
If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.
Founder Bio:
Jason is presently serving as the Co-founder and Chief Technology Officer at Xembly, where he leverages years of expertise in adeptly crafting software products rooted in cutting-edge technologies such as Artificial Intelligence, Machine Learning, Virtual and Augmented Reality, Speech Recognition, Audio Signal Processing, and Streaming Media. As a founding member of both the Microsoft Xbox Kinect and HoloLens teams, he played a pivotal role in groundbreaking innovations, notably contributing as the primary inventor of open microphone, no push-to-talk speech recognition. With a remarkable portfolio boasting 40+ patents in conversational AI and natural language innovations, Jason brings a wealth of knowledge to the tech industry. He holds a Master's degree in Engineering from the University of Miami.
Time Stamps:
01:48 Introduction and background of Jason Flaks
08:17 Pain points that lead to creating Xembly
14:00 How Calendly works well in a lopsided marketplace but not in an organization
18:26 The focus on solving the end-to-end lifecycle problem
22:43 Differentiating between AI and language models
24:20 AI challenges in identifying speakers in a room
26:19 Challenges of building a dialogue system for group negotiations
29:30 Importance of planning, negotiation, and decision-making in AI systems
31:50 Hiring resources for AI product development
35:40 Importance of expertise in conversational AI for feature generation
38:41 Benefits of domain expertise in building AI systems
40:04 Getting the right person for the right job
44:06 What new updates can we expect from Xembly in 2024
47:24 How to get in contact with the Xembly TeamResources
Company website: https://www.xembly.com/
Twitter: https://twitter.com/MeetXembly
LinkedIn: https://www.linkedin.com/company/xembly/
Instagram: https://www.instagram.com/meetxembly/ -
The rise of online learning platforms like Coursera and Udemy has created a massive demand for learning new skills. However, the completion rates on these platforms have been disappointingly low, with only 1% to 2% of learners actually finishing a course. This is due to the lack of personalization and the absence of support for learners who may have different backgrounds and prerequisites.
Korbit recognized this problem and set out to create a solution that would address the individual needs of learners. Their initial approach was to build an e-learning platform that used AI to personalize the learning experience. However, they soon realized that even with personalization, learners still struggled to identify what skills they needed to learn and how to apply them in their jobs.
In this episode, we sit with Iulian Vlad, CEO and Co-founder of Korbit. Iulian shares his journey from being a math and AI enthusiast to working on personal assistants for Amazon's Echo device. He discusses the pain points in online learning and workforce training, highlighting the lack of personalization and the disconnect between learning and job requirements. Iulian explains how Korbit's AI mentor platform solves these issues by providing personalized, in-context learning within the workflow of software engineers. He also discusses the challenges of remote work and the importance of building a strong team culture.
If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.
Founder Bio:Iulian is the founder of Mila spin-off Korbit, a startup on a mission to transform the future of work and learning on the job. Korbit is building an AI Mentor for Software Engineering which does code reviews and just like a senior engineer detects issues and explains how-to fix them. The AI Mentor can detect over 10,000 issues from critical bugs and security vulnerabilities to code architecture and performance issues. The AI Mentor then trains the software engineering team to resolve them. The result: teams ship code better, faster and accelerate their code review process by 10x while improving code quality and upskilling engineers.
Iulian completed his Ph.D. in Artificial Intelligence and his Master's in Computer Science and Computational Statistics. He is the winner of the C2 Emerging Entrepreneurs Award and NeurIPS Competition Award, and is an alumni of the Mila research lab with over 20 peer-reviewed scientific papers and books published to date. Iulian was the employee #1 of Copenhagen startup DigiCorpus building AI for healthcare solutions. There he developed from scratch their AI-powered physiotherapy solution and launched it into the market.Time Stamps:
02:06 Julian’s background in AI and his work on personal assistants
06:00 The pain point in workforce training and learning
09:52 Companies’ struggle to identify future skill needs
12;48 Korbit’s approach to personalized learning and relevancy
15:00 Building an AI mentor product that identifies needs and delivers targeted Micro lessons.
20:25 Why technical founders struggle to attract business people and vice versa.
22:44 Managers often don’t know what their team needs or the skills their team members hav.
24:37 Training must focus on real issues, not management’s assumptions
27:26 Using data from code repositories and comments to identify issues and make recommendations
30:52 Prioritizing privacy by deleting source code and offering a self-hosted solution
33:37 Remote team and best practices for remote work using the product internally
37:01 Fundraising journey for an AI startup
40:48 Challenges of AI startups and competition with OpenAI
42:15 Languages Supported By the Engineer AI mentor
44:16 What coming up, contact information, and how to learn more about KorbitResources
Company website: https://www.korbit.ai/
LinkedIn: https://www.linkedin.com/company/korbit-tech/
Facebook: https://www.facebook.com/KorbitTech/
Twitter: https://twitter.com/Korbit_Tech -
Today we sit with Michael Simpson, the founder of Pairin; a company that uses AI to connect individuals to relevant resources and career opportunities. With a background in the technology industry, Michael has always been involved in cutting-edge technologies and has a passion for leveraging AI to solve complex problems. He shares his journey and the inspiration behind creating Pairin, a platform that helps individuals navigate their careers and make informed decisions. With AI-driven features like resume and cover letter creation, Pairin aims to provide personalized guidance and improve the job search process. Michael emphasizes the importance of AI in constantly improving and adapting to user needs, ultimately helping individuals find success in their chosen paths.
AI fulfills people’s desires by providing instant answers and enabling them to do things they couldn’t do on their own. Pairin’s product is a framework that allows institutions to build customized workflows and conversations with individuals to help them make wise decisions and navigate their career paths.
If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.
Founder Bio:
Michael is a son of educators, and corporate intrapreneur turned 3x entrepreneur. His passion for helping people reach their potential was fuelled by his rise from poverty to international recognition as a market strategist. He co-founded PAIRIN after over a decade as a certified coach and spent seven years living in Russia coaching many at-risk young adults to successful careers. As the CEO of PAIRIN, he works to bridge the opportunity gap for future generations by making every person’s career and education journey more relevant and attainable.
Under Michael’s leadership PAIRIN, founded and based in Denver, CO, has received numerous awards, including the 2023 Inc. Fastest-Growing Company, BuiltIn’s 2023 & 2022 Best Places To Work for Small Colorado Companies, 2021 EdTech Breakthrough Award for College Prep Company of the Year, Business Insider’s 50 Coolest Companies in America, Outside’s 50 Best Places to Work in 2021, 2019 and 2018, Denver Business Journal’s Best Places to Work in 2019, the 2017 Denver Chamber of Commerce Start-Up of the Year, the 2017 Colorado Technology Association APEX Emerging Tech Company of the Year award and 2017 Colorado Companies to Watch winner.
Time Stamps:
01:55 Introduction and background of Michael Simpson
06:13 The pain point that led to the creation of Pairin
12:03 The problem Pairin solves: connecting people to relevant resources
13:55 Designing workflows to guide individuals through career decisions
16:41 Selling to state agencies, workforce organizations, and trade associations
18:36 Using AI avatars and resume/cover letter creator
21:17 How descriptive AI educates users in resume and cover letter creation
25:35 Managing algorithms to bypass employment gaps
28:23 Building technology with a diverse team of experts
30:26 Vetting AI companies to ensure their technology is genuine
33:12 Integrity and truthfulness in AI companies
34:18 Identifying patterns in large datasets with AI
36:30 The difference between traditional software and AI products
39:40 Contact information and how to learn more about Pairin
Resources
Company website: https://www.pairin.com/
LinkedIn: https://www.linkedin.com/company/pairin-inc-/
Facebook: https://web.facebook.com/PairinInc
Twitter: https://twitter.com/Definedai -
In the realm of artificial intelligence (AI), data plays a crucial role. In essence, it serves as the backbone of AI, providing the necessary nourishment to the algorithms and models that power intelligent systems. As AI continues to evolve, data will remain a primary focus to ensure the continued growth and success of intelligent machines.
In this episode we sit with Daniela Braga, CEO and Founder of Defined AI. Daniela discusses her journey in AI and the pain point she set out to solve. She explains how her background in linguistics led her to work on the first text-to-speech system in European Portuguese and voice assistants for Microsoft. Daniela saw the need for data at scale, especially in local languages, and founded Defined AI to address this problem. The company offers a crowdsourcing platform and a marketplace for training data, ensuring responsible AI and machine learning readiness. Daniela also shares her thoughts on the future of AI, the challenges of data collection, and the impact of regulations on the industry.
With the increasing usage of AI in our lives, the ethical implications of data collection and AI algorithms come into focus. Dr. Braga emphasizes the importance of responsible AI and the need for companies to be transparent about how they collect and use data. Defined AI takes a proactive approach to ensure that the data it collects is consented and properly vetted.
If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.Founder Bio:
Dr. Daniela Braga is the founder and CEO of Defined.ai, one of the fastest-growing startups in the AI space. She has been the recipient of several awards, including the E&Y Entrepreneur of the Year Pacific Northwest 2020 Award, #27 Deloitte Fast 500 2020 (#1 in the Pacific Northwest region); #27 in Inc.5000 in 2020, and Goldman Sachs Most Intriguing 100 Entrepreneurs in 2021. She is a member of the World Economic Forum’s Expert Network as a Tech Pioneer and AI Expert in WEF Davos 2022. She’s also a YPO and a Chief member. Dr. Braga has raised over $80 million of Venture Capital, making her the woman founder in AI who has raised more capital in the world. Dr. Braga has been appointed to the National Artificial Intelligence (AI) Research Resource Task Force, a 12-person body that advises the US president on the AI strategy of the United States. She is also an advisor to the President of Portugal.
Time Stamps:
02:20 Introduction and background of Daniela Braga
06:19 Importance of local languages and inclusivity in AI
09:50 Limitations of data availability in generative AI
11:47 Utilizing crowdsourcing and synthetic data for AI training
14:21 Acquisition and processing of specific data for AI solutions
17:54 Advantages of the data lake and metadata extraction
20:56 Discussion on proprietary data and its use in AI solutions
23:43 Awareness of data usage and government regulations
28:12 Potential shift towards paying for data protection and meaningful content
29:39 OpenAI’s growth, Microsoft deal, and potential regulation
32:22 Lack of reverse engineering measures and outdated information in AI search results
34:29 Defined AI’s use of AI internally
37:40 Daniela Braga’s experience raising VC capital
40:17 How to learn more about Defined AI
Resources
Company website: https://defined.ai/
LinkedIn: https://www.linkedin.com/company/definedai/
Twitter: https://twitter.com/Definedai -
Artificial intelligence (AI) has become a household term, and its applications are revolutionizing various industries. One area where AI is making a significant impact is heavy industry, including manufacturing, energy, and utilities. In these sectors, companies often face the challenge of outdated digital infrastructure, which hampers productivity and data quality. However, the emergence of conversational AI is changing the game by streamlining processes and improving efficiency.
In this opportunity we speak with Mark Fosdike, the CEO & Co-founder of Datch, a company that specializes in conversational AI solutions for heavy industry. Mark's background in aerospace and his firsthand experience with the challenges faced by frontline workers in heavy industry inspired him to develop a solution that would revolutionize the way data is captured and processed. In our conversation, Mark shared insights into the journey of building Datch and the transformative power of conversational AI.
If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.
Founder Bio:
Mark Fosdike, CEO of Datch, is a visionary leader in the field of asset management and a dedicated entrepreneur. With over two decades of industry experience, Mark has an exceptional understanding of the challenges and opportunities in asset management, and a proven track record of driving innovation and growth.
Before founding Datch, Mark held several senior leadership positions in renowned global companies, where he gained extensive expertise in industrial operations, and technology. His passion for delivering cutting-edge solutions led him to establish Datch, with the aim of revolutionizing asset management through the integration of advanced AI-driven features.Time Stamps:
01:54 Mark’s background before creating Datch
04:14 Identifying the problem of inefficient data input in heavy industry
06:20 How Datch uses conversational AI to speed up processes and improve data quality
09:13 Adaptability of Datch's interface for frontline workers
10:40 Leveraging large language models for accurate speech-to-text and prompt engineering
13:12 Customization and application to specific use cases
15:48 Approach to acquiring new customers
17:55 Typical sales cycle and stakeholders involved
19:34 Changing interest in AI solutions over time
22:59 Mark discusses the need for a consultative sales approach
24:38 Founders' background and passion for building things
28:21 Importance of building a network and finding advisors
29:58 Getting advisors to buy in with equity and commitment
32:30 Hiring strategy and the importance of hungry generalists
34:01 Fundraising journey and challenges as a first-time founder
37:58 Exciting things coming up in the future
38:53 How to get in contact with the Datch teamResources
Company website: https://www.datch.io/
Twitter: https://twitter.com/datchsystems
LinkedIn: https://www.linkedin.com/company/datch/
Facebook: https://web.facebook.com/Datch.io -
In this episode, we interview Dilip Mohapatra, the CEO, and founder of Cognitive View, a company that uses AI to solve compliance and customer complaint issues in regulated industries. We discuss how their AI technology is helping businesses in regulated industries monitor and analyze customer conversations to ensure compliance and improve customer service. He shares how the idea for Cognitive View came about and the challenges they faced in building their AI solution.
Dilip explains the importance of understanding complex legal requirements and how their AI model can identify compliance breaches in customer conversation. He also discusses the value of generative AI and the unique capabilities its offers. Dilip highlights the metrics they use to measure the success of their ai solution, including reducing compliance and conduct risk by up to 70% and reducing customer complaints by 50%. He also touches on the fundraising journey for cognitive view and the importance of finding investors who can provide value beyond just capital
If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.
Founder Bio:
Dilip Mohapatra is the founder of Cognitive View, a regtech company that creates solutions that monitors communication and collaboration channels to automate compliance, quality, customer experience, and conduct risk. It provides the necessary tools to create a customer-centric culture and risk-based supervision that automates operational risk. Cognitive View has been recognized as RegTech100 globally; AI Fintech 100; the best vendor solution for Managing Conduct Risk at the Regtech Insight APAC Awards 2021; and a 2021 IBM Beacon Award Finalist. Dilip has successfully built an enterprise software channel business with IBM and held a variety of product management roles, including HP, Hyro, and Ipedo.
Time Stamps:
01:58 Background of Dilip and Cognitive View
04:05 Challenges faced by companies in managing compliance and misconduct
05:11 Monitoring conversations and identifying compliance breaches with AI
07:36 The importance of understanding complex legal requirements in AI models
10:28 Use cases of Ai in voice, video, and text conversations
12:29 Target industries and metrics for ROI
15:30 Building the Ai solution and the importance of talent
18:03 Challenges in accessing data and the use of proprietary data
22:01 Proof of concept process and requirements for customer engagement
27:01 Leveraging generative AI and proprietary data for unique solutions
30:45 Providing contextual and industry-specific AI solutions
34:33 Fundraising journey and the value of investors
36:56 Talent sourcing ante importance of distributed teams
38:49 Balancing privacy and data sovereignty in a distributed company
42:00 How to get in contact with the Cognitive View team
ResourcesCompany website: https://www.cognitiveview.com/
Twitter: https://twitter.com/cognitiveviewai
LinkedIn: https://www.linkedin.com/company/cognitiveview/
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Artificial Intelligence (AI) has revolutionized how businesses operate, and supply chain management and insurance are no exceptions. With the ability to analyze vast amounts of data and identify patterns, AI has the potential to transform supply chain operations and insurance claims management, making them more efficient, cost-effective, and responsive to customer demands. In this thought leadership article, we explore the power of AI in supply chain management and insurance.
In this episode, we sit with Stan Smith CEO of Gradient AI. Stan has founded six companies and has been working with machine learning and AI since the late 1990s. Stan shares his experiences working with AI and machine learning, starting with his first startup that focused on supply chain management. He discusses how his company used machine learning to predict which suppliers were likely to have issues and how this helped his clients save millions of dollars. Stan also talks about the pain point he saw in the insurance market and how Gradient AI is assisting businesses to leverage AI to solve complex problems and improve their operations. In this episode, Stan also talks about the importance of equity in startups, the challenges of building AI solutions in the insurance industry, and the measures Gradient AI took to ensure client data was secure.
If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.
Founder Bio:
Stan Smith is the Founder and CEO of Gradient AI. Stan founded Gradient AI, first as a unique practice within Milliman to focus on the risk management and insurance industry’s most challenging business problems. He acquired the business from Milliman in 2018, founding Gradient AI as a rapidly growing independent SaaS organization. With nearly 30 years of experience growing AI and technology organizations, Stan’s leadership ensures that Gradient AI is applying the latest Artificial Intelligence and Machine Learning technologies to the insurance industry, resulting in proven financial performance for its stellar list of customers and better treatment and outcomes for individuals. Stan has held founding or executive-level roles for multiple startup companies, including Vice President at MatrixOne, Executive Vice President and General Manager at Agile Software, and CEO and Founder at OpenRatings.Stan also led the development of patented technologies including: technology that predicts bankruptcies for small, privately held suppliers; a global database to improve supplier performance for more than 80 million companies; and, technology that combines assessments with performance data to identify opportunities for reducing inefficiencies through lean initiatives.
Time Stamps:
02:17 Stan Smith's background and experience in the startup world
06:15 Paint point that led to the idea for Gradient AI
09:04 Importance of identifying high-risk claims early
12:18 Ability of Gradient AI's models to accurately predict the cost of a claim
14:32 The complementary nature of AI and human adjusters in claims processing
17:07 Engaging with clients in underwriting operations
19:52 Integration of Gradient AI solutions into commercial systems
23:40 Challenges of building AI solutions in the insurance industry
25:11 Importance of having a team with both AI and insurance expertise
27:14 The importance of culture and team in attracting talent
29:36 Incentives that Gradient AI offers to attract the right talent
32:51 Educating insurance companies about AI and the impact of the pandemic
37:29 Turning interest in AI into investible business problems
40:14 Fundraising journey and partnerships with insurance-focused venture capitalists
41:57 Selecting investors based on industry and AI experience
43:44 Whats coming up new for Gradient AI
44:10 How to get in contact with the Gradient AI team
Resources:
Company website: https://www.gradientai.com/
Twitter: https://twitter.com/GradientAI1
Facebook: https://www.facebook.com/gradientai/
LinkedIn: https://www.linkedin.com/company/gradientai/
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In this episode, we sit with Dr. Karim Galil, the founder and CEO of Mendel.AI, an artificial intelligence-powered platform that extracts insights from medical records to improve patient outcomes. Dr. Galil shares his journey from practicing medicine to becoming a tech entrepreneur and the role that AI can play in making healthcare more data-driven. He discusses the challenges of subjective medical practices and the potential for AI to learn from every patient's journey.
Dr. Galil explains that symbolic AI is more focused on teaching machines fundamentals of logic, rules, and concepts, while machine learning is more focused on learning from patterns. He gives an example of the opioid crisis, where a machine learning model would learn that opioids are great because humans are prescribing them, while a symbolic system would understand what opioids are and what the best options are. In the process of building AI in healthcare, Mendel.AI has used both symbolic AI and machine learning. Dr. Galil also discusses the challenges of talent acquisition in the AI industry and how the economy can impact AI talent availability. He emphasizes the importance of hiring talent with grit, curiosity, and coachability and the benefits of hiring mid-level to junior talent to assist the genius.
Mendel.AI is a healthcare platform that uses symbolic AI and machine learning to provide personalized treatment plans for patients. The platform reads every medical record and encounter between patients and healthcare systems to help physicians make more objective decisions. Mendel.AI works with big pharmaceuticals, payers, and data companies to help them read their data and glean insights to make better decisions. The platform can help pharmaceutical companies understand which patients respond better to what drug and in what occasions, and payers can decide whether to cover a certain medication or not. Mendel.AI uses domain experts to learn from, rather than just data and can help pharmaceutical companies discontinue drugs that are not effective and optimize their drug offerings.
If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.
Founder Bio:
Dr. Karim Galil, MD, is the CEO and Co-founder of Mendel.AI. Mendel's mission is to learn from every patient by structuring and de-identifying patient data at a machine scale and human fidelity to power clinical and research use cases. Dr. Galil’s experience as a physician demonstrated that medicine does not advance at the same rate as technology. With Mendel, he aims to bridge this gap, facilitate clinical research at scale, and make medicine objective. Dr. Galil’s expertise in AI, medical informatics, and digital health makes him a sought-after presence at global conferences.
Time Stamps:
01:49 Introduction of Dr. Karim Galil and his background in medicine
06:59 The potential for AI to learn from every patient's journey
10:41 The challenges of working with unstructured medical data
12:19 The importance of explainable AI in healthcare
15:20 Using real-world data to identify drug effectiveness in specific patient profiles
18:02 The difference between machine learning and symbolic AI
21:09 Difference in talent and approach needed for symbolic AI vs machine learning
23:02 The process of building concepts for symbolic AI
25:53 Challenges of talent acquisition in the AI industry
27:49 The impact of the economy on AI talent availability
31:49 The importance of hiring talent with grit, curiosity, and coachability
35:18 Building a competitive advantage and a mode in AI startups
38:53 Challenges of finding the right investors for AI startups
41:51 The myth of VCs being a value add and the importance of cash and brand
43:01 Who is the end user and how do they engage with the product
45:49 How to get in contact with the Mendel team
Resources:
Company website: https://www.mendel.ai/
Twitter: https://twitter.com/mendel_ai_
Facebook: https://www.facebook.com/mendelai/
LinkedIn: https://www.linkedin.com/company/mendel-ai
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Today we sit with Michael D. Abramoff, a neuroscientist and the founder of Digital Diagnostics, a company that leverages artificial intelligence (AI) to provide autonomous medical diagnosis. In this interview, Michael shares his background and how he got into AI, as well as his vision for the future of medical diagnosis. He discusses how he uses AI to make medical diagnoses, the challenges he faces, and the potential for AI to revolutionize healthcare. He also talks about his involvement in other AI-related projects and his thoughts on the ethical implications of AI in healthcare. In addition, Michael delves into the safety concerns surrounding AI, particularly with language learning models (LLMs), and the importance of ensuring that AI is safe and free of bias.
Michael’s vision for AI in healthcare goes beyond mere assistance or augmentation of human decision-making. He believes that AI can make diagnoses and treatment decisions autonomously, without the need for human intervention. However, the promise of autonomous AI must be balanced with the potential pitfalls. As he pointed out, AI that learns from biased or fallible humans can produce models that are worse off. In healthcare, this could lead to harm to patients if doctors blindly follow AI recommendations.
Digital Diagnostics is a company that uses AI to diagnose diabetic retinopathy and increase healthcare access for underserved patients. The AI is trained to detect specific lesions using clinical knowledge and chunk by chunk learning to avoid bias. Healthcare providers can approve or disapprove the AI's recommendations, and the company aims to supplement rather than displace professionals.
If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.
Founder Bio:
Michael D. Abramoff, MD, PhD, is a fellowship-trained retina specialist, computer scientist, and entrepreneur. He is Founder and Executive Chairman of Digital Diagnostics, the first company ever to receive FDA clearance for an autonomous AI diagnostic system. To transform the quality, accessibility, and affordability of global healthcare through the automation of medical diagnosis and treatment. In primary care, it can instantaneously diagnose diabetic retinopathy and diabetic macular edema at the point of care. Dr. Abramoff developed an ethical foundation for autonomous AI that was used during the design and validation, and regulatory and payment pathways for autonomous AI. As the author of over 350 peer-reviewed publications in this field, he has been cited over 42,000 times, and is the inventor of 20 issued patents and many patent applications. Dr. Abramoff has mentored dozens of engineering graduate students, ophthalmology residents, and retina fellows. His passion is to use AI to improve the affordability, accessibility, and quality of care.
Time Stamps:
02:10 Michael's background as a neuroscientist and his interest in AI
05:37 Safety concerns surrounding AI, particularly with LLMs
07:08 The challenges of implementing AI in healthcare
09:07 The importance of AI supporting decision making rather than making decisions
11:02 The potential for AI to revolutionize healthcare
15:25 The importance of ensuring access to healthcare for all
18:40 The pain points behind creating Digital Diagnostics
21:49 Creating an ethical framework for regulation and reimbursement of AI
24:02 Potential for AI to outperform human experts in diagnosing medical conditions
26:00 Importance of clinical outcomes: acquiring data for AI and ensuring inclusivity
29:26 The impact of pigmentation on AI training data
31:37 Talent shortage in AI: transition from rule-based systems to machine learning
33:00 Understanding the fundamentals of AI despite increased efficiency
35:10 The need to prove the worth of AI in healthcare through clinical outcomes
37:24 How to get in contact with the Digital Diagnostics team
Resources:
Company website: https://www.digitaldiagnostics.com/
Facebook: https://www.facebook.com/AItheRightWay
LinkedIn: https://www.linkedin.com/company/digital-diagnostics
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