The Darius Gant Show

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

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

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

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

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/rollbarCompany 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/

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 2024

Resources

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/