The Tesoro AI Podcast

In this episode of the podcast, we talk to Bryton Shang, an engineer, and technologist with a background in operations and financial engineering from Princeton. Bryton has been a co-founder and CTO of multiple tech startups, with his latest venture, Aquabyte, utilizing artificial intelligence to detect sick animals in fish farms. Bryton discusses the challenges facing the fish farming industry and how technology can be used to overcome them. He talks about the use of cameras and computer vision AI models to help fish farmers monitor the growth and welfare of their fish, and how this data-driven approach can lead to increased sustainable food production.   We also learn about the benefits of using Aquabyte's technology system for fish farmers. This system allows farmers to measure the growth of their fish over time, make decisions on their food and treatments, and harvest them earlier for a higher price. Bryton explains how the system was approved by the FDA in Norway, eliminating the need for manual counting and handling of the fish, increasing the quality of the fish that is consumed, and making business processes more effective.   Finally, Bryton touches on the global nature of the fish farming industry, highlighting its presence at a fish expo in Brussels, where every type of fish imaginable was present. Join us as we explore the exciting world of technology in fish farming and its potential to revolutionize the industry.   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: Bryton Shang is the founder and CEO of Aquabyte, which uses computer vision, machine learning, and AI to help aquaculture farms feed the world as cleanly and efficiently as possible by giving the industry unprecedented insight into the health, growth, and sustainability of their fish. Bryton grew Aquabyte from an idea with a prototype in his bathtub to an intelligent camera and data platform that helps the world's top fish farms understand what's happening in their pens -- uniquely identifying individual fish to track their health, growth, and environment -- without removing the fish from the water. Its technology solutions include biomass estimation, sea lice counting and non-antibiotic treatment optimization, feed optimization, welfare indicators, and more. All of this helps aquaculture farms minimize waste and maximize profit while also protecting the fish, waters, and communities that depend on them. The company now operates offices in Norway, the U.S., and Chile, and was the first technology company to be recognized for its accuracy by the Norwegian Food Safety Authority. Prior to Aquabyte, Bryton led several venture-backed startups, including as CTO of HistoWiz. At this biotechnology firm, he developed a deep learning algorithm to diagnose cancer, as well as iQ License, a brand licensing platform that he co-founded. Bryton graduated at the top of his engineering class at Princeton University and was recognized by Forbes magazine as a 30 Under 30 leader in Manufacturing & Industry. When he's not at a fish farm, you can find him in San Francisco.   Time Stamps: 02:06 Bryton’s background and professional journey 05:09 Exploring the use of AI in fish farming 09:28 Benefits of fish farming and the use of technology for healthier fish 13:29 Aquabyte’s AI-native solution for fish farming + 16:43 Challenges of collecting training data for AI solutions in fish farming 20:16 Implementing AI solutions for farm growth measurement 22:42 Building a multidisciplinary team to solve computer vision problems in the marine biology industry 25:22 Recruiting for data labeling, AI, and computer vision experts 29:56 Recruiting strategies for a mission-driven startup 33:08 Challenges of growing a startup 37:18 Challenges of growing a business 40:51 How to get in contact with the Aquabyte team   Resources: Company website: https://aquabyte.ai/ Facebook: https://web.facebook.com/aquabyteai LinkedIn: https://www.linkedin.com/company/aquabyte/ Twitter: https://twitter.com/aquabyteai

In this episode of the podcast, we sit down with Igor Jablokov, an artificial intelligence expert who has had a long and varied career in the industry. We discuss the emerging technology of multimodal interfaces, which allow users to choose from different modes of input and output, and how consumer tech companies have been able to package this technology and make it accessible to the mass market. We delve into the world of entrepreneurship and the stereotypes associated with the industry. Igor talks about his experiences founding and running his own companies, including his latest venture, Pryon. He also shares his thoughts on the importance of education and foresight when looking at the industry.   Throughout the episode, Igor shares his unique perspective on the intersection of art and science, drawing on his childhood in Greece and his teenage years in Philadelphia and Montreal. We discuss his role in creating voice-activated experiences, and how he was inspired to launch his latest venture, Alexa.   We also touch on the importance of accuracy and security in the development of AI technology, particularly in environments like hospitals, where lives may be on the line. Finally, we explore the impact of social media on the spread of information, and the importance of accuracy in the age of Twitter.   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:   Igor is the CEO and Founder of Pryon. Named an “Industry Luminary” by Speech Technology Magazine, he previously founded industry pioneer Yap, the world’s first high-accuracy, fully-automated cloud platform for voice recognition. After its products were deployed by dozens of enterprises, the company became Amazon’s first AI-related acquisition. The firm’s inventions then became the nucleus for follow-on products such as Alexa, Echo, and Fire TV. As a Program Director at IBM, Igor led the team that designed the precursor to Watson and developed the world’s first multimodal Web browser. As an innovator in human language technologies, he believes in fostering career and educational opportunities for others entering STEM fields. As such, he serves as a mentor in the TechStars’ Alexa Accelerator, was a Blackstone NC Entrepreneur-In-Residence (EIR), and founded a chapter of the Global Shapers, a program of the World Economic Forum.     Time Stamps:   02:18 Igor's professional journey and background 04:51 Benefits of multimodal technology for end users 07:42 Intersection of art and science in voice technology 12:41 What is Pryon, what does it do? 18:38 AI-powered document analysis for enterprises 20:22 Benefits of separating duties and leveraging expertise in product development 25:23 Benefits of AI technology for enterprise and cognitive technologies for businesses 31:12 Leveraging AI technologies to achieve growth 33:23 Evolution of AI technologies and their impact on business 35:29 Discussion on generative technologies and responsibilities 38:51 Exploring the impact of generative AI on critical needs and consumer tech companies 41:37 Risks of not advancing ai technology 44:56 Generative technologies and their impact on privacy and commerce 47:27 How to get in contact with the Pryon team Resources:   Company website: https://pryon.com/ Instagram: https://www.facebook.com/pryoninc LinkedIn: https://www.linkedin.com/company/pryon/ Twitter: https://twitter.com/pryon  

In this episode, we delve into the captivating career path of Ernest Chan, the Founder, and CEO of PredictNow.AI. Despite starting with a degree in physics, Chan has made a name for himself in the world of finance and machine learning. With experience from working at IBM Research in natural language processing, machine learning, and speech recognition, to developing groundbreaking methods to compare identities without an exact match while working in an internal consulting unit at Morgan Stanley, Chan has a wealth of knowledge to share.   We also explore Chan's foray into the hedge fund industry, following in the footsteps of some of his former colleagues who had become billionaires at Renaissance Technologies. After working at Credit Suisse and starting his own startup during the dot-com bubble, Chan eventually found success in the hedge fund industry once again before catching the entrepreneurial bug once more in 2005.   PredictNow.AI believes that the potential of machine learning lies in its ability to correct human decisions rather than make them from scratch, hence the term Corrective 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:   Ernest Chan (Ernie) is the founder and CEO of PredictNow.AI, a machine learning SaaS. He started his career as a machine learning researcher at IBM's T.J. Watson Research Center's Human Language Technologies group, which produced some of the best-known quant fund managers. He later joined Morgan Stanley's Data Mining and Artificial Intelligence group. He is the founder and non-executive chairman of QTS Capital Management, a quantitative CPO/CTA. He obtained his Ph.D. in physics from Cornell University and his B.Sc. in physics from the University of Toronto.   Time Stamps:   01:55 Ernest Chang's early career and Background 04:02 Exploring the intersection of finance and machine learning 06:33 From Morgan Stanley to starting a startup: an early work in the fintech industry 10:09 Challenges of launching a new product in an unprepared market 12:57 Becoming an independent trader and launching a fund 17:33 Using corrective AI to improve investment decisions 20:32 Benefits of AI-augmented investment decision making 23:32 Clustering AI predictive variables for improved decision making 28:07 Leveraging data to build a practical ai system 33:30 Benefits of AI-powered trading with Predictnow.AI 35:00 Benefits of conditional portfolio optimization for institutional investors and Asset managers 41:15 AI product development and raising capital for a quantitative asset management firm 44:08 What’s coming up in 2023 for PredictNow.AI 46:17 How to get in contact with the PredictNow.AI team Resources:   Company website: https://predictnow.ai/ Youtube: https://www.youtube.com/@predictnowai6002 LinkedIn: https://www.linkedin.com/company/predictnow-ai/ Twitter: https://twitter.com/PredictNowAI  

In this episode, we dive into the world of AI-powered customer support with Deon Nicholas, CEO and Co-founder of Forethought. Deon shares his journey into the field of AI and how his passion for technology led him to start his own company. He explains how Forethought's natural language processing technology is transforming the customer conversation experience by providing customers with quick and accurate answers to their questions. Deon discusses the history of natural language understanding and processing, and how it has evolved over the years. He explains how chatbots have been used for customer service but were often clunky and unsatisfactory for customers. He then shares how Forethought's approach to chatbots is different and how their innovation is providing a better experience for customers.   The conversation delves into the differences between decision tree makers and AI-powered chatbots, with Deon highlighting the limitations of manual and keyword-based systems. He explains how Forethought's technology is based on language models that are built using historical customer inquiries and the actions taken by customer service agents, providing a more detailed and accurate understanding of customer inquiries.   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:  Deon Nicholas is CEO & Co-Founder of Forethought, one of the leading generative AI platforms for customer support automation. The company has raised over 90 M in venture capital from 42 investors, including LL Cool Jay, Sean “Diddy” Combs, Gwyneth Paltrow, Ashton Kutcher, Baron Davis, Robert Downey Jr., owner of the Utah Jazz, Ryan Smith and Vlad Tenev, CEO of Robinhood. Mr. Nicholas grew up in Toronto, Canada, where as a teenager he fell in love with computers and video games. He went on to study computer science at the University of Waterloo and interned at Facebook and Palantir. He then worked at Dropbox and Pure Storage, where he developed a passion for solving technically difficult problems. He also has ML publications and infrastructure patents, was a World Finalist at the ACM International Collegiate Programming Contest, and was named to Forbes 30 under 30.  Time Stamps:  02:12 Deon background and early career into AI 04:34 Evolution of natural language understanding and AI-powered chatbots 06:57 Difference between Chat GPT and Forethought AI technology 10:49 Integrating language models into customer service: challenges and solutions 13:39 Possibilities of applying transformer models to customer service data sets 15:23 Benefits of AI-powered support interactions for high growth companies 21:10 Semi-supervised learning for automated customer support 24:05 AI-powered chatbot solutions for improved customer support 27:19 Benefits of AI for businesses: Discussion on economies of scale and cost savings 30:31 Understanding the difference between AI and human-under-the-hood businesses 37:23 Benefits of combining deep ML research and product development 39:34 Investing in an AI business: building a team of engineers for AI product development 42:50 How to get in contact with the Forethought team Resources: Company website: https://forethought.ai/ Facebook: https://www.facebook.com/forethought.tech/ LinkedIn: https://www.linkedin.com/company/forethought-ai/ Twitter: https://twitter.com/forethought_ai  

In this episode of the Darius Gantt Show, we sit with Gary Saarenvirta, the founder and CEO of Daisy Intelligence, to discuss his journey in the world of autonomous AI and the challenges and successes of building a company that revolutionizes decision making. Gary is a preeminent expert on autonomous AI, and his company has pioneered explainable decisions as a service for merchandise planning and risk management. This technology is transforming the way retailers and insurers make data-driven decisions. Gary's background in numerical methods and machine learning led him to be one of the first worldwide users of IBM's machine learning product, and he eventually left IBM to found Daisy Intelligence.   Gary discusses how his company's technology is similar to how Neil Armstrong gave the computer instructions to land the lunar module, with the human setting the objective and the computer taking care of the details. He also covers the importance of control theory and system thinking when it comes to successfully leveraging AI. Gary highlights the use of control theory in the aerospace industry and explains how it is essential to wrap machine learning and predictive modeling in control theory to create stable and fault-tolerant AI systems.   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:   Gary Saarenvirta is a Canadian engineer, scientist, speaker, and entrepreneur. Saarenvirta is best known for being the founder and CEO of the Canadian Artificial Intelligence (AI) company Daisy Intelligence. In 1992, Saarenvirta worked as an Object-oriented_programming software development consultant for three years at METEX, known for selling forth generation software development platforms. For the following five years, he was the general manager of data analysis consulting at The Loyalty Group, best known for their Air Miles program. In 2000, Saarenvirta joined IBM as the head of data mining and data warehousing practices until 2002, when he then moved on to become the chief operating officer at Adastra Corporation until 2003. In 2003, Saarenvirta began his entrepreneurship, founding Makeplain Corporation on December 22nd. In 2016, the company was rebranded, and became what is known today as Daisy Intelligence.   Time Stamps:   02:22 Gary Background and origins of AI in Toronto 05:20 Benefits of AI and machine learning 09:42 Autonomous decision making in fraud detection and retail merchandise planning 13:20 Leveraging technology to support employees 16:25 Exploring the benefits of AI-driven technologies for content creation 18:55 Benefits of autonomous AI software for businesses 23:34 Danger of a data-driven approach in business and engineering systems 26:08 Optimizing retail merchandise planning decisions 27:59 Benefits of predictive modeling and change management in retail planning 30:53 Building trust through AI 33:05 Change management and AI implementation considerations 35:05 Automating data cleaning for ai development 36:44 Hiring for machine learning team in a data science company 39:07 Retaining talent in a startup scale up: strategies for success 42:30 Discussion on the safety of Chat GPT and Google ads systems 44:33 How to get in contact with the Daisy Intelligence team   Resources Company website: https://www.daisyintelligence.com/ LinkedIn: https://www.linkedin.com/company/daisyintelligence/ Twitter: https://twitter.com/daisyintel

Calling a business should not be a frustrating experience where you're forced to endure terrible hold music and struggle to reach a human representative. In this episode, we sit down with Alex Sambvani, CEO and Co-Founder of Slang.AI, to discuss how AI is transforming customer service. Slang.AI utilizes voice AI technology to create personalized, interactive conversations with customers, revolutionizing phone-based customer service. With a background in mechanical engineering and business, Alex has always been interested in technology and entrepreneurship. After working in finance for several years, he returned to tech and eventually landed at Spotify as a data scientist. It was there that he began working on voice technology and was inspired to start Slang AI with his co-founder, Gabe.   Throughout the podcast, Alex discusses the potential of AI in customer service and the challenges businesses face in implementing it. They also explore the frustrating experience of calling businesses and how Slang AI is working to make it easier for businesses to incorporate voice technology into their customer service strategies.   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:   Alex first became interested in technology when he learned to code at the age of 14 (self-taught). Since, he has spent his career hopping back and forth between engineering and business. He spent several years working in private equity investing and more recently worked as Senior Data Scientist at Spotify. Alex is passionate about applying artificial intelligence to challenging societal problems. He holds a B.S. in Mechanical Engineering from Stanford and an MBA from Harvard.   Time Stamps:   02:17 Alex background and how It was introduced to AI 07:55 What is Slang.AI and the potential of voice technology for businesses 10:12 Transforming the experience of calling a business 13:37 Conversation flow sample for flame 15:09 Impact of Chat GPT on voice and NLP applications 19:30 AI product architecture: challenges of building an AI business 24:03 Collecting data to train AI models for a new company 28:13 Building a team with subject matter expertise for ai and machine learning 31:00 Upskilling and AI combining technical and subject matter expertise 33:10 Funding journey for Slang.AI: raising capital for a voice AI startup 40:51 Upcoming launches and fundraises for 2023 42:40 How to get in contact with the Slang.AI team Resources   Company website: https://www.slang.ai/ Instagram: https://www.instagram.com/sandrosambvani/ LinkedIn: https://www.linkedin.com/company/slang-ai/ Twitter: https://twitter.com/slang_ai  

One of the stand-out characteristics of Artificial Intelligence (AI) is its ability to learn, for better or for worse. It’s this ongoing effort that distinguishes AI from static, code-dependent software. It’s also precisely this ability that makes high-quality annotated data a crucial element in training representative, successful, and bias-free AI models.   In this episode, we sit down with Jason Liang, VP of Business Development and Co-founder of SuperAnnotate. This AI lifecycle platform provides annotation services and training data for machine learning models. With over a decade of experience in finance, corporate, and tech startups, Jason brings a unique perspective to the conversation. We start by exploring Jason's background, including his experience at Lehman Brothers and his time in the tech world at SAP's mobile division. From there, we dive into the SuperAnnotate platform and how it helps companies build high-quality datasets for machine learning. Jason explains how SuperAnnotate uses professionally managed annotation teams instead of crowdsourcing to ensure high data quality.   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 Liang is the VP of Business Development and a Co-founder of SuperAnnotate where his goal is to help every organization radically improve the way they build, manage, and leverage datasets for machine learning unlocking limitless value in their data. Jason has a decade of experience leading go-to-market activities for ML companies such as Qeexo and DataRobot. Jason also spent time at SAP, as the Executive Director for Global Solutions. Jason began his career in investment banking at Lehman Brothers. He has an MBA from UC Berkeley's Haas School of Business and a bachelor's degree from MIT. Jason is also an advisor for a number of startups and is a go-to-market advisor for Berkeley's SkyDeck incubator.              Time Stamps:   00:00 Jason's background: from finance to AI startup founder 03:30 Exploring data annotation and labeling with super annotate 06:15 Leveraging professional annotation teams to streamline data labeling processes 09:50 Data engineering solutions for AI companies of all sizes 12:23 Data annotation and machine learning workflows for fortune 500 companies 13:53 Managing data for fortune 500 companies: challenges and solutions 17:11 AI development consulting services 18:16 Exploring go-to-market strategies for early-stage startups in computer vision and NLP 22:13 Leveraging software and training to outperform specialized agronomists 23:29 AI adoption and SuperAnnotate fundraising journey 26:00 Potential of generalized machine learning and AI infrastructure 29:32 Regulations and ethics in artificial intelligence deployment 31:32 Discussing data security and compliance 32:55 How to get in contact with the SuperAnnotate team Resources: Company website: https://www.superannotate.com/ Facebook: https://www.facebook.com/superannotate LinkedIn: https://www.linkedin.com/company/superannotate/ Twitter: https://twitter.com/superannotate  

Today we sit with Andrew Palmer, founder of Bertha AI, to discuss the revolutionary tool that uses ChatGPT and OpenAI to create compelling marketing copy and images in a fraction of the time it would take to do it manually. In this conversation, Andrew talks about his entrepreneurial journey prior to Bertha AI, which includes developing a web hosting management solution for agencies, advocating for product makers, and providing plugin development support. Andrew then shares his experience with Bertha, a plugin and Chrome extension that generates text and copywriting for a variety of online platforms.   Bertha was designed to help solve the pain point of content generation and gathering, which is often difficult to get from clients. Bertha was built as a writing assistant for website developers and provides prompts related to website development, such as unique services, unique sales propositions, product descriptions, and other text. But it also can be used in WordPress, Shopify, and other E-commerce, making it a versatile tool for content creation. The plugin can generate product descriptions, blog post topics, and other content. It also includes images to help with the development of websites.   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:   Andrew Palmer is one of the co-founders of Bertha AI. He is providing WordPress users with an easy solution for content creation, maintaining a daily connection with the WordPress community and offering coaching, advocacy, and support for individuals and companies striving for excellence. Additionally, he endorses GridPane, a company offering a fantastic hosting management solution for agencies to start, manage, and provide great hosting services to their clients. Andrew is also the founder of WP Plugins Plus, a company with locations in London, UK, and Kolkata. WP Plugins Plus specializes in making plugins, providing support for various agencies, and offering guided website design and build services.     Time Stamps:   02:33 Background of Bertha: from vendor marketplace to AI-powered writing tool 05:55 AI-powered content generation for clients 07:25 Benefits of Bertha: a WordPress plugin for writing assistance 11:27 Approaching to build Bertha: a conversation on AI-powered content creation 13:28 AI development and mitigating risk with open-source solutions 15:26 Benefits of AI-powered chatbot development 19:21 Benefits of prompt engineering for ai applications 23:19 The core skills of a prompt engineer 27:26 Mechanics of large language models with OpenAI 29:27 Bertha AI ability to ask relevant questions. 33:13 Benefits of chat GPT and Bertha for code development 35:06 The impact of generative AI on open source and privacy rights 38:57 Strategies for creating value for monetizing. 40:44 Using Bertha AI for increasing productivity and profitability 43:10 How to get in contact with the Bertha.AI team Resources   Company website: https://bertha.ai/ Facebook: https://www.facebook.com/groups/berthaai LinkedIn: https://www.linkedin.com/in/andrewpalmer/ Twitter: https://twitter.com/BerthaAI_  

Historically, breeding has been a blend of science and chance – a lengthy, expensive process where outcomes often come with tradeoffs. As one plant characteristic such as yield is optimized, another such as protein content is compromised. CropOS changes this by enabling greater control and precision, this means reduced costs and greater accessibility. In this episode of the podcast, we sit down with Jason Bull, the Chief Technology Officer of Benson Hill, to discuss the company's focus on producing healthier and more sustainable food options with the help of its Crop OS platform. With over 20 years of experience at Monsanto, Jason is now bringing his expertise to Benson Hill, where he leads the company's R&D, data science, predictive breeding, genomics, product discovery, big data engineering, and software development. Jason shares his experience in transitioning from traditional breeding to molecular assisted breeding and then to predictive breeding. He talks about how he put in place the underlying systems to run research and development, and how he began working with predictive technologies, eventually leading to the integration of AI at Monsanto. The conversation delves into the executive decision to use artificial intelligence to predict future outcomes, and how Jason had to prove the worth of AI to the business owners. Jason addresses the internal concerns around job security and how the team overcame these challenges by having food scientists, data scientists, and plant scientists all work together. 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 Bull is the Chief Technology Officer of Benson Hill. In his role as CTO, Jason leads the company’s combined R&D and Data Science capabilities across predictive breeding, genomics, product discovery, big data engineering and software development. Bull has over 20 years of industry experience unlocking synergies between biology and data science for multiple industries. Bull spent twenty years with Bayer (Monsanto) and then Climate Corporation, most recently as its Global VP R&D of Digital Seed Science, where he delivered a digital advisory platform. Jason has been granted 30 patents in digital agriculture, molecular breeding and robotic seed chipping. He has also authored 15 publications on the optimization of breeding and production systems. He earned his Ph.D. in Quantitative Genetics and Biometrics and a BA in AgSci (Honors) in Quantitative Genetics and Analytics from the University of Queensland in Australia.    01:49 Jason Bull background: AI in Monsanto's Seed Development Process 05:32 Artificial intelligence to increase success in product development 06:45 Benefits of cross-functional teams for AI Implementation 12:14 Jason experience with machine learning at object computing OCI 16:39 Exploring a new opportunity in biotech genetics and food science 18:56 Benson Hill AI-Inspired platform and products 24:02 Jason's role in accelerating Benson Hill expansion 27:44 Scaling the organization with ai and machine learning talent 30:07 Recruiting talent for AI and machine learning at Benson Hill 32:08 Benefits of across functional team and SWAT teams for AI delivery 36:32 Discussion on Crop OS and organizational decisions at Benson Hill 39:05 What’s next for Benson Hill AI development 41:07 Combining Impact, Cost, and AI to Create Innovative Products 43:20 How to get in contact with the Benson Hill team   Resources Company website: https://bensonhill.com/ FaceBook: https://www.facebook.com/BensonHillInc LinkedIn: https://www.linkedin.com/company/bensonhill/ Twitter: https://twitter.com/bensonhillinc

Today we sit down with Pascal, the founder, and CEO of Bardeen AI, a leading workflow automation company. Pascal shares his journey in the AI and machine learning field, and how his experience of spending too much time on repetitive tasks led to the creation of Bardeen, a platform designed to automate micro functions for users. They discuss how Bardeen integrates AI into its platform to understand user needs and recommend the right automation for the right user in the right context. He shares everyday use cases for Bardeen, such as market research, outreach, and recruiting, and how it is integrated with popular tools like Notion, AirTable, and Google Sheets.   Bardeen automates manual work so that people can focus on what they love. It also allows you to trigger and participate in automation right from where you are. This idea of contextual, proactive automation unlocks the potential of automating tasks that previously only large companies with big budgets could and now takes just a few minutes to set up.   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:    Pascal started his career at the intersection of ML and neuroscience, trying to learn how to learn the brain. He then went on to work with Google Brain on various ML projects, and then founded and successfully exited an AI company in the AgTech space. After his exit, he helped co-found an NGO and then went on to start and lead Telefonica's Moonshot Factory's AI team. In 2019 he joined Augustus Intelligence to build the tools and platform to enable real scale for AI and ML use-cases in the enterprise. He is currently based in NYC and is also actively investing and advising various AI companies as a Venture Partner at AI Capital and personally.  01:58 Pascal Weinberger's background, from recruiting to automation tools to BAE  04:59 Pain point of repetitive tasks 06:46 Automating repetitive tasks with workflow automation 10:44 exploring the journey of building an ai model 14:30 Benefits of solving problems without ai before training a model 17:18 Shift from model-first to business value-first ai solutions 19:57 Abstraction layer for automating automation 22:04 Hiring for a tech company: challenges and strategies 25:54 Discussion on the engineering hiring market in 2021 28:22 Go-to-market strategies for automation platforms 32:37 Benefits of automation with Bardeen 36:06 ROI metrics for ai automation solutions 38:11 AI company raises series funding to automate end-user workflows 41:23 How to get in contact with the Bardeen team Resources:   Company website: https://www.bardeen.ai/careers YouTube: https://www.youtube.com/c/Bardeenai LinkedIn: https://www.linkedin.com/company/bardeen/ Twitter: https://twitter.com/bardeenai