Humans of AI

In this episode of Humans of AI, host Sheikh Shuvo sits down with Dan Lesovodski, the co-founder of Data Monsters, to explore his journey in the world of artificial intelligence. Dan shares his early experiences with AI, the inception of Data Monsters, and the company's role as an AI incubator. He provides an in-depth look at the challenges of evaluating AI technology, the bottlenecks in the AI development lifecycle, and the impact of AI on Data Monsters' operations. Throughout the conversation, Dan emphasizes the importance of focusing on projects with real value, understanding the complexities of AI, and redesigning systems to fully leverage AI capabilities.

Key Takeaways:

• AI methods have been used for decades, but the recent AI hype has led to a rebranding of these methods.
• When working with AI, it is important to focus on projects with real value and consider the maturity level of the company.
• Understanding the complexities and limitations of AI is crucial for successful implementation.
• Redesigning existing systems and processes is necessary to fully leverage the capabilities of AI.
• Creating a culture of value, sustainability, and creativity is important for attracting and retaining AI talent

In this episode of Humans of AI, Varun Khare, CEO of NimbleEdge, discusses the transformative impact of edge computing. NimbleEdge is revolutionizing technology by moving intelligence from the cloud to handheld devices, enhancing efficiency and user experiences. The conversation covers the challenges of integrating edge computing, NimbleEdge's specialization in gaming and e-commerce, and its integration with existing cloud services. Varun also shares insights into the rise of large language models, NimbleEdge's focus on the US market, and upcoming product releases.

Key Highlights:

• NimbleEdge improves efficiency and user experiences by moving intelligence from the cloud to handheld devices.
• Challenges in edge computing include handling device diversity and optimizing applications for different devices.
• Specialization in gaming and e-commerce improves conversion metrics and user engagement.
• Integration with existing cloud services ensures seamless transition and compatibility.
• The rise of large language models has boosted the positioning of edge computing.
• The US market focus is on optimizing user experiences in mobile apps.
• Upcoming releases include a Python VM for Android and iOS and more efficient models.

In this episode of Humans of AI, Sam Awrabi, Vice President of Global Sales at Nomic, takes listeners from his origins in political science to his impactful role in tech and AI sales. Sam shares the challenges and rewards of leading sales in startup environments and how he selects promising startups to work with. He introduces Nomic's innovative machine learning platform, transforming how enterprises manage unstructured data.

Sam also discusses founding his venture capital firm, focusing on AI-native startups, and the unique sales process required for AI products compared to traditional software. He stresses the importance of leveraging the open-source community for building trust and enhancing product adoption.

Closing with advice for those aiming to break into AI sales, Sam highlights flexibility, continuous learning, and adaptability as key to success in the evolving AI industry.

Key Insights:

• The journey from political science to leading AI sales.
• Evaluating startups with potential for impact.
• Nomic's role in advancing unstructured data analysis.
• The strategic approach to selling AI projects.
• Leveraging open-source for growth and trust.
• Tips for aspiring AI sales professionals.

Join us to gain valuable perspectives from a leader at the intersection of sales and AI innovation, guiding the future of enterprise data solutions.

Summary

Reid Blackman, Founder and CEO at Virtue Consultants, shares his background in philosophy and how he transitioned to advising on ethical AI. He discusses the inspiration behind starting Virtue and the early projects he worked on. Reid emphasizes the importance of self-education on the technical details of machine learning. He also explores the relevance of philosophical schools of thought to AI ethics and the types of questions and requests he receives from clients. Reid discusses the urgency of ethical AI considerations for government clients and the differences in priorities based on company sovereignty. He concludes by sharing his personal approach to using AI tools in his own workflows.

Takeaways

• Self-education is crucial for understanding the technical details of machine learning and AI ethics.
• Ethical AI considerations should go beyond legal compliance and focus on reputation and responsible practices.
• Different clients have different priorities, ranging from regulatory compliance to being best in class.
• Government clients are taking ethical AI seriously, but most organizations are self-creating their own standards.
• The use of AI tools in workflows depends on individual expertise and the need for personal style and judgment.

Summary
Jason, an academic, researcher, and entrepreneur, discusses various topics related to computer science, AI, and entrepreneurship. He shares insights on changes in student interest and research topics, the impact of social applications on teaching style and curriculum design, and the recruitment of faculty for the robotics department at the University of Michigan. Jason also discusses inflection points for computer vision, the importance of physically grounded computer vision, and the founding of his company, Voxel 51. He shares customer stories and reflects on the New York Times copyright infringement case against OpenAI.

Takeaways

• There is a growing interest among students in making a positive impact and bringing about change through AI and computer science.
• The popularity of computer vision has led to changes in teaching style and curriculum design, with a focus on social applications.
• Recruiting faculty for robotics departments involves emphasizing lasting, sustained societal impact and collaboration.
• The future of computer vision lies in physically grounded scenarios and the ability to generalize from past experiences.
• Assessing the trustworthiness of datasets is an important challenge, and metrics for dataset quality and bias need further development.
• Building a startup requires a focus on impact and a willingness to learn and adapt to user needs.
• Voxel 51 has had a positive impact on teams, helping them discover mistakes in datasets and saving time on tool development.
• The New York Times copyright infringement case against OpenAI raises important questions about the ownership and use of data and models.

Summary
Martyn Redstone, an expert in conversational AI, discusses his career journey, the evolution of mobile communications, and his passion for communication and conversational AI. He shares insights on the challenges of training and implementing conversation tech, the shift in customer requests for AI tools, and the recruiting workflows that are not easily replaced by AI. He also highlights the transferable skills needed for transitioning into AI roles and discusses innovative trends in conversation tech. Lastly, he talks about how he introduces AI to his children and the future of work.

Takeaways

• Martyn Redstone started his career in sales and operations before transitioning to HR and recruitment.
• The evolution of mobile communications has been a significant part of Martyn's career, from analog to digital to the current voice-driven technology.
• Martyn is passionate about communication and conversational AI, which led him to explore the use of AI in recruitment processes.
• Implementing conversation tech can be challenging, with pushback from people and the need for post-implementation learning and onboarding.
• The future of work will involve AI-powered careers, and there is a need for conversation designers and prompt designers in the AI field.
• The conversation tech industry is experiencing a shift towards a hybrid approach combining NLU and large language models.
• It is important to introduce AI to children and educate them about its capabilities and limitations.
• AI tools like transcription tools and large language models are useful in workflows, but there are still aspects of recruiting that require human involvement.

Summary
In this podcast episode, Sheikh Shuvo interviews Will, an accomplished research scientist and tech executive. Will shares his journey in the field of AI, from his early interest in computer graphics to his eventual focus on computer vision. He discusses the hype and public awareness surrounding AI and how it has evolved over the years. Will also talks about his favorite project at Snap and the impact of company culture on research. He provides insights on evaluating companies as a research scientist and offers advice for PMs and software engineers transitioning into AI. The conversation concludes with a discussion on risk assessment and management in AI and Will's current projects in healthcare.

Takeaways

• The field of AI has experienced significant hype and public awareness in recent years, with the community gaining exposure to the masses in a political campaign-like manner.
• Company culture plays a crucial role in shaping the direction of research and development, with different companies having distinct approaches and priorities.
• When evaluating companies as a research scientist, factors such as ethics, product focus, and the founders' background and leadership style should be considered.
• For PMs and software engineers transitioning into AI, it is important to understand the technology and its use cases, as well as the product-market fit.
• Risk assessment and management are critical in AI, especially in areas like generative AI, and organizations should invest in cybersecurity measures to protect against potential threats.
• Will is currently working on projects in healthcare, using AI to improve healthcare systems, provide insights, and develop software solutions for sensitive populations like inmates.

Summary
In this conversation, Jan, an experienced talent acquisition professional, discusses his career journey and the use of AI tools in recruiting workflows. He shares insights on developing AI bots for interaction and highlights the challenges AI faces in understanding human nuances. Jan also discusses the importance of retaining AI talent and identifies emerging regions for AI talent. He concludes by providing advice for candidates from non-AI backgrounds.

Takeaways

• Choosing companies based on the people and opportunities can lead to a successful career in talent acquisition.
• AI tools like ChatGPT and video creation tools have been useful in Jan's recruiting workflows.
• Developing AI bots for interaction can challenge one's thoughts and opinions, leading to new perspectives.
• Real empathy is difficult for AI to mimic, making it a challenging aspect for AI to play a role in recruiting.
• Retaining AI talent can be achieved by providing flexibility, competitive pay, purpose, and a supportive team.
• The US and India are significant players for AI talent, but running AI startups can be expensive.
• Non-AI background candidates can focus on learning machine learning and how to write effective prompts for AI applications.

Summary
In this conversation, Sheikh Shuvo interviews Venkat Ramesh, a hardware systems engineer at Meta. They discuss various aspects of AI hardware and its impact on the industry. Venkat shares his background and inspiration for working in this field. He also talks about his experience at Meta and the company's involvement in the open source community. They explore overlooked elements of AI hardware, such as networking, cooling, and fault tolerance. Venkat discusses the challenges in optimizing heat and cooling in AI systems. He also mentions the AI debugging toolkit and the need for hardware-level monitoring and telemetry. Venkat shares his approach to recruiting and building teams, emphasizing the importance of adaptability and problem-solving skills. He talks about using AI tools in his own workflows and the potential for AI in education. Finally, Venkat shares his wish list for the AI industry in 2024, focusing on the use of AI in personalized learning and education.

Takeaways

• AI hardware includes various components beyond GPUs, such as networking, cooling, and fault tolerance.
• The AI industry is evolving rapidly, and standards are being formed to address the challenges of AI hardware.
• Recruiting for AI hardware teams requires individuals who can handle ambiguous problems and work collaboratively.
• AI tools, such as AI debugging toolkits, can be helpful in optimizing workflows and staying up to date with the latest advancements.
• The future of AI in education holds potential for personalized learning and optimization of the learning process.

Summary
In this conversation, Matthew discusses his background in private equity and his transition into the tech industry. He explains the concept of data preparation to a five-year-old and shares his first professional experience with AI. Matthew also talks about his involvement with Next Step and Africa AI, as well as his current work at Cogito Tech. He emphasizes the importance of compliance and governance in the data industry and discusses the potential impact of a higher minimum wage on the AI industry. Matthew draws inspiration from the sales and UI industries and shares advice for his younger self.

Takeaways

• Data preparation can be compared to setting up stations in a kitchen and organizing ingredients before cooking a meal.
• Transitioning from private equity to tech requires a shift in focus from managing multiple companies to dedicating oneself to one company.
• The impact of AI regulations on sales cycles emphasizes the need for more consultative and involved sales approaches.
• Compliance and governance are crucial in the data industry, and companies like Cogito Tech are working to provide transparency and best practices.
• Drawing inspiration from the sales and UI industries can provide valuable insights for managing teams and launching successful products.

Summary

In this conversation, Jade Newton discusses her work in the field of AI, her transition from marketing to AI, and the changes she has observed in the industry. She also talks about the importance of data annotation and the role of human labor in AI development. Jade shares her research in social linguistics and the focus on African-American vernacular English. She emphasizes the need for diversity in AI development and highlights her work with Feminist AI and Poyetto in promoting ethical AI. Jade also discusses her involvement in EdTech and her passion for educating others about AI. Finally, she touches on AI regulations and the need for detailed implementation.

Takeaways

• Transitioning to AI requires a willingness to learn on the job and seek out self-education.
• Data annotation is a crucial part of AI development, but companies are exploring ways to automate and bring it in-house.
• Diversity and inclusion are essential in AI development to ensure ethical and responsible AI.
• Education and awareness are key in promoting responsible AI and incorporating it into various sectors, including EdTech.
• AI regulations, such as the EU AI Act, are important steps towards ensuring ethical AI development.

Summary

In this conversation, Vino Duraisamy, a data engineer and developer advocate at Snowflake, shares her journey and insights in the field of data engineering. She explains the concept of data engineering to a five-year-old, discusses her spark of interest in the field, and highlights the importance of explainable AI. Vino also talks about her passion for writing tutorials and creating content, the role of a developer advocate, and the challenges of building and managing a community. She shares her excitement about the advancements in AI tool and platform development, particularly in the area of responsible AI. Finally, Vino offers advice for new data engineers, emphasizing the importance of building a strong foundation and staying updated with industry trends.

Takeaways

• Data engineering can be explained to a five-year-old as the process of collecting and analyzing data to make sure there are enough toys for everyone in a toy shop.
• Explainable AI is an important field that helps understand how AI models make decisions and ensures transparency and accountability.
• Writing tutorials and creating content can be a valuable way to share knowledge and help others in the industry.
• Developer advocacy involves engaging with the developer community, providing feedback to product teams, creating content, and staying updated with industry trends.
• Responsible AI and the challenges of deploying and managing LLMs (large language models) are areas of focus in AI tool and platform development.
• New data engineers should focus on building a strong foundation in programming and data engineering concepts, while also staying updated with industry trends and acquiring additional skills.

Join us in this episode of the Humans of AI Podcast, where host Sheikh Shuvo sits down with Atul Dhingra, a Machine Learning Engineer specializing in Generative AI at PayPal. Dive into the intricate world of AI as Atul shares his journey from an undergrad in Delhi to the forefront of AI technology. 

Explore three key highlights:

• Atul's unique insights into transitioning from academic research to industry applications
• his perspective on the evolving landscape of ML startups and big tech,
• and his forward-looking thoughts on the emerging importance of ML security ops.

Don't miss Atul's invaluable advice on team-building and innovation in the fast-paced world of AI. Tune in to gain a deeper understanding of the AI revolution and be inspired by the possibilities it holds for our future. Listen now and join the conversation on the frontiers of AI!

In this episode of Humans of AI, we engage with the Upol Ehsan, a leading figure in the realm of AI. 

Highlights of our conversation include:

• Seamful Design in AI: Upol introduces the innovative concept of seamful design in AI, underscoring its significance in enhancing human-centric AI applications.
• Human Influence in AI: Delving into the human aspect of AI, Upol sheds light on how human interactions and choices are integral to AI's impact and development.
• Cross-Disciplinary Inspirations: Upol shares how his unique approach to AI is influenced by diverse fields, ranging from historical literature to the science fiction of Isaac Asimov.

Join us for a thought-provoking journey that connects the dots between AI technology and human experience. Subscribe to Humans of AI for more engaging discussions and insights into the world of Artificial Intelligence!

In this episode of the Humans of AI Podcast, host Sheikh Shuvo interviews Ketan Umare, exploring his extensive career in developing distributed systems across various industries. Ketan recounts his early experiences in anti-money laundering software development and his journey through high-performance computing, leading to his work at Citadel in high-frequency trading. He reflects on his time at Amazon, Oracle, and Lyft, emphasizing the importance of infrastructure in data science and machine learning. The conversation delves into Union, a company Ketan co-founded, focusing on its evolution, open-source contributions, and the challenges of educating the market about AI and ML platforms.

Takeaways:

• Ketan's career journey is marked by diverse experiences across different industries, highlighting the evolving nature of distributed systems.
• His work at Citadel and Amazon provided unique insights into high-frequency trading and large-scale system architectures.
• At Lyft, he contributed significantly to the development of Union, addressing the gap in machine learning infrastructure.
• Union's focus on open-source development and community engagement plays a crucial role in its growth and user adoption.

In this episode of Humans of AI, Megan Dibble, a data journalist, shares her journey from industrial engineering to data analysis and her role at Alteryx. She discusses the importance of trust in data and how Alteryx enables reliable analytics for everyone. Megan also talks about her experiences hosting the Alter Everything podcast and the surprising insights she has gained from interviewing data practitioners. She shares her process for finding inspiration for her data journalism work and highlights the areas of data science she is currently focused on. Megan concludes by offering advice for early career data analysts.

Takeaways

• Data journalism involves creating content about all things data, using various mediums such as writing, podcasting, and social media.
• Choosing a career in data analysis can involve inflection points, where individuals discover their passion for working with data through internships and job experiences.
• Data analysts and journalists should prioritize trust in data by using tools that provide transparency and governance, and by starting projects with clear business problems.
• The Alter Everything podcast has revealed the diversity of backgrounds in the data field and the importance of starting data projects with a clear business problem.
• Data journalists find inspiration from various sources, including courses, reading publications, and their day-to-day work experiences.
• Areas of focus in data science include data ethics, bias in algorithms, and the limitations of quantification.
• Early career data analysts should avoid taking on the weight of an organization's data structure and instead focus on building relationships with IT and data engineering teams.

In this episode of the Humans of AI Podcast, host Sheikh Shuvo engages with Mark Freeman, Tech Lead at Gable, to explore the dynamic intersections of data science, AI, and career development. 

Highlights of this episode include:

• Mark's unique journey from sociology to becoming a tech leader in data science, emphasizing the importance of diverse academic backgrounds in the tech industry.
• Deep insights into the concept of data contracts and how they are revolutionizing data governance, particularly in AI applications.
• Mark’s candid reflections on career progression in the tech world, offering valuable advice for both practitioners and leaders in the field.

Don't miss this episode for a comprehensive view of AI’s evolving landscape and valuable career insights. Listen now and join the conversation on how data is shaping our world!

In this episode of the Humans of AI Podcast, host Sheikh Shuvo converses with Matt Dancho, Co-Founder at Quant Science, delving into the fascinating world of data science and AI.

Highlights of this episode include:

• Matt's journey from starting in data science to founding Business Science and Quant Science, detailing the pivotal moments and inflection points that shaped his career.
• The development and impact of TidyQuant, Matt's innovative software library, and its role in transforming data analysis in finance and beyond.
• Insightful discussions on the intersection of generative AI and supply chain management, and how Matt is guiding companies like Quantex in solving real-world problems.

Join us for this compelling conversation and gain valuable insights from a leader in the field. Don't forget to subscribe for more inspiring stories from the frontiers of AI and data science!

Join us in this episode of the Humans of AI Podcast as we delve into the mind of Egor Pushkin, Chief Architect, Data and AI at Oracle. Explore the evolving landscape of artificial intelligence through the eyes of a seasoned expert.

In this episode, Egor shares his journey from academia to leading AI innovations, offering unique perspectives on:

• The transformation of neural networks and the rise of generative AI technologies.
• The challenges and strategies of implementing AI in enterprise and healthcare sectors.
• Egor's personal approach to staying at the forefront of AI advancements and his passion for driving change in the field.

Don't miss out on this enlightening conversation that bridges the gap between technological development and practical application. Tune in, get inspired, and discover the future of AI with Egor Pushkin. Subscribe now for more engaging conversations with AI luminaries.

In this episode of the Humans of AI Podcast, host Sheikh Shuvo engages in a deep conversation with Kush Varshney, a distinguished research scientist and senior manager at IBM's Watson Research Center. They delve into the intellectual and career journey of Kush, shedding light on his groundbreaking work in the realm of trustworthy machine learning.

Highlights of this episode include:

• Insights into AI Colonialism: Kush Varshney discusses the colonialism of AI, analyzing Western values in AI development and advocating for inclusivity and global perspectives in AI technology.
• The Evolution of AI and Ethics: The episode covers Kush’s thoughts on ethical AI development, focusing on fairness, explainability, and robustness in machine learning, and the role of AI in societal good.
• Future Directions in AI Research: Kush shares his vision for the future of AI, touching upon his work with foundation models, the importance of empathetic AI, and the delicate balance between safety and creativity in AI applications.

This episode is a must-listen for anyone interested in the intersection of AI, ethics, and societal impact.