The Tesoro AI Podcast

Brian Rue, CEO and co-founder of Rollbar, shares his journey from building social games on Facebook to revolutionizing error monitoring. He discusses how Rollbar leverages AI to proactively discover and fix coding errors, improving developer productivity. The conversation highlights the transformation of error detection, enabling teams to focus on critical issues without sifting through volumes of reports. Brian also touches on the challenges of integrating AI in team workflows and the influence of current market dynamics on AI companies.

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/

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/  

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 Team Resources 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 Korbit Resources 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