When we think about legal tech software, we think about value add discovery or document management. But with the explosion of AI, new opportunities are emerging. We're going to share a story about how technology can help lawyers help more people and you'll hear a word that might surprise you too: Justice.

On this episode of the Georgian Impact Podcast, we'll be talking with the founders of one of Georgian's investments, a fascinating company with an absolutely wonderful name for a company in this space, Darrow. But, it's not the name that matters today. It's about an idea and the coming together of a vision.

You'll Hear About:

Who are the Co-Founders of Darrow?

Evyatar Ben Artzi is the Co-Founder and CEO at Darrow.ai. Evyatar harnesses his legal and technological experience to improve legal systems and societies, empowering people to make better decisions and become the authors of their own story. Evyatar assumed leadership roles in the collaborative and dynamic teams he has led and worked with, whether as a Combat Officer in the IDF, a clerk at the Israeli Supreme Court, as a Co-Founder of Yahav – a progressive education program – or as Co-Founder and CEO at Darrow, using AI to unearth the legal implications of real-world events.

Gila Hayat is the Co-Founder and CEO at Darrow.ai. Prior to Darrow, she spent seven years in computer intelligence in the IDF, in part, focusing on classified projects on ethical issues of AI both in the military and police forces. She and her team earned presidential honors for their work.

We all get a few chuckles when autocorrect gets something wrong, but there's a lot of time-saving and face-saving value with autocorrect. But do we trust autocorrect? Yeah. We do, even with its errors. Maybe you can use ChatGPT to improve your productivity. Ask it to a cool question and maybe get a decent answer. That's fine. After all, it's just between you and ChatGPT. But, what if you're a software company and you're leveraging these technologies? You could be putting generative AI output in front of your users.

On this episode of the Georgian Impact Podcast, it is time to talk about GenAI and trust. Angeline Yasodhara, an Applied Research Scientist at Georgian, is here to discuss the new world of GenAI.

You'll Hear About:

Who is Angelina Yasodhara?

Angeline Yasodhara is an Applied Research Scientist at Georgian, where she collaborates with companies to help accelerate their AI products. With expertise in the ethical and security implications of LLMs, she provides valuable insights into the advantages and challenges of closed vs. open-source LLMs.

Sometimes it’s hard to know where to start when it comes to generative AI. It’s not too hyperbolic to say that many different aspects of a business have the potential to be affected by this new technology. Today, we’re going to talk about something that’s behind the scenes for most people, although hopefully not this audience. It’s coding.

On this episode of the Georgian Impact Podcast, we dive into the world of generative AI and its impact on coding, testing, and product design with guest Rodrigo Ceballos. Rodrigo is a Machine Learning Engineer at Georgian and provides firsthand experience and expertise, shedding light on the transformative power of AI in the tech industry. Exploring the exciting possibilities brought about by the fusion of human creativity and AI technology.

You’ll Hear About:

Who is Rodrigo Ceballos?

With over six years of experience in AI research and engineering, Rodrigo Ceballos is a dedicated Machine Learning Engineer at Georgian. In his current role, Rodrigo collaborates with portfolio companies to implement solutions in computer vision, natural language processing and generative AI. Before joining Georgian, he served as an AI Research Engineer at PAIGE.ai, where he played a pivotal role in developing PaigeProstate, the world's first FDA-approved AI-assisted pathology diagnostic tool.

We’ve all heard about how generative AI is changing almost every aspect of a business. If you crack open the door and peer in on the AI teams. You’ll see them playing with models and, no, we’re not talking about planes and trains. We’re talking about providing the correct inputs necessary to drive desired outputs in an AI model.

On this episode of the Georgian Impact Podcast, we will be discussing the impact of generative AI and fine-tuning data strategy with Rohit Saha, an ML scientist at Georgian’s R&D team. Rohit will explore how large language models (LLMs) and fine-tuning are changing the AI landscape for businesses, the necessary skills for data science teams in the age of generative AI, and the pivotal role of dynamic data strategy in leveraging new technology effectively.

You’ll Hear About:

Who is Rohit Saha?

Rohit Saha is an ML Scientist at Georgian's R&D team. He works with the portfolio companies to accelerate their data science roadmap by assisting them in scoping research problems, writing machine learning or AI code, and putting solutions into production. Rohit has worked across various projects, specializing in computer vision, natural language processing and large language models. His expertise lies in helping companies fine-tune and leverage large language models for enterprise software solutions.

Sometimes it’s hard to know where to start when it comes to generative AI. It’s not too hyperbolic to say that many different aspects of a business have the potential to be affected by this new technology. Today, we're going to talk about something that's behind the scenes for most people, although hopefully not this audience. It's coding.

On this episode of the Georgian Impact Podcast, we dive into the world of generative AI and its impact on coding, testing, and product design with guest Rodrigo Ceballos. Rodrigo is a machine learning engineer at Georgian and provides firsthand experience and expertise, shedding light on the transformative power of AI in the tech industry. Exploring the exciting possibilities brought about by the fusion of human creativity and AI technology.

You’ll Hear About:

• The progression of software engineering from low-level to high-level languages, culminating in the use of natural language for coding.
• The daily integration of generative AI, such as ChatGPT, in automating tasks and writing code.
• The role of large language models (LLMs) as an intermediate layer and a translation layer between different pieces of software.
• The impact of generative AI in automating functions, unit testing, and API interaction in programming.
• Using generative AI to brainstorm and guide game design, showing the versatility of AI in enhancing human creativity.
• The potential upside and downside of leveraging generative AI in streamlining processes and increasing efficiency.

We've all heard about how generative AI is changing almost every aspect of a business. If you crack open the door and peer in on the AI teams. You'll see them playing with models and, no, we're not talking about planes and trains. We're talking about providing the correct inputs necessary to drive desired outputs in an AI model.

On this episode of the Georgian Impact Podcast, we will be discussing the impact of generative AI and fine-tuning data strategy with Rohit Saha, an ML scientist on Georgian's R&D team. Rohit will explore how large language models (LLMs) and fine-tuning are changing the AI landscape for businesses, the necessary skills for data science teams in the age of generative AI, and the pivotal role of dynamic data strategy in leveraging new technology effectively.

You’ll Hear About:

• The role of fine-tuning in tailoring foundational AI models to specific use cases.
• How the landscape of ML and AI has evolved with the emergence of LLMs.
• Leveraging LLMs to enhance productivity and build enterprise software.
• Evolution of skills and talent required in the era of generative AI.
• Creating a dynamic data strategy and leveraging open source models for fine-tuning.
• Identifying golden use cases and the impact of LLMs on classification tasks.

Generative AI is redefining businesses with its capacity to write text, generate code, execute tasks, create images, and more. Gen AI is fundamentally changing how companies have to build their products.

This is the first in a series of podcasts featuring our AI team, where they share their experiences on the generative AI work they've already done with more than 20 of our portfolio companies. In this episode, we are joined by two technical leaders of Georgian's R&D team Parinaz Sobhani and David Tingle. Parinaz is the Head of AI at Georgian and David is the team's Engagement Manager for our work with our customers. 

You’ll Hear About: 

• How generative AI is reshaping businesses by excelling in text, code, task execution, and image generation.
• The importance of a cross-functional collaboration approach and a top-down problem-solving strategy in technology development.
• An overview of the historical focus of Georgian's AI team on data and machine learning.
• Exploration of the starting points for companies, including the use of foundational models from big tech companies and the role of first-party data in differentiation.
• Discussion on the crawl, walk, run stages of generative AI adoption, highlighting the importance of finding a golden use case and the need for a "trust-first" approach for future-proofing.

On this episode of the Georgian Impact podcast, we are talking to a guest we last had in 2020. Back in 2020, we were talking about AI and marketing and how to use things like automation tools to make our jobs easier. Now in 2023, generative AI tools are basically the biggest topic of conversation right now. So, we're here to break that down with Paul Roetzer.

Paul is the author of several books on marketing and AI, including Marketing Artificial Intelligence, and he's the creator of the Marketing AI Conference.

You'll Hear About:

• The evolution of generative AI tools in marketing.
• The role of AI in ideation and strategy, rather than writing.
• The adoption and integration of AI tools into marketing workflows.
• The impact of generative AI on content creation and strategy.
• Building an AI council within organizations.
• Developing responsible AI principles and policies.
• The importance of a moral compass in AI application.
• Transparency and disclaimers for AI usage.
• The future of AI in entrepreneurship, creativity and scientific breakthroughs.
• Addressing fears and concerns related to AI in the workplace.

On this episode of the Georgian Impact podcast, we’ll be breaking down the technologies that make up generative AI and how it works. From Large Language Models (LLMs) to deep learning, this podcast will help you understand how AI has evolved to get us to this point with GenAI and what he’s excited about in the space.

Mahan Salehi, AI and LLM product manager at NVIDIA, will explain how the space has evolved from his experience at NVIDIA working with AI. 

You’ll Hear About:

●  Machine learning vs. artificial intelligence.

●  The need for guidance for GenAI models.

●  Rules-based models vs. deep learning models.

●  The two pieces of generative AI.

●  How foundational models are trained.

●  The value of first-party data.

●  Mahan looking back and looking forward.

●  The impact on different industries.

Since our inception, Georgian has identified new trends that we believe will change the way companies do business. This kind of thinking resulted in our thesis areas like Applied AI, Conversational AI and Trust.

In this episode of the Georgian Impact Podcast, we talk to Sonia Lagourgue, Georgian’s Head of Purpose & ESG and Emily Walsh, Lead Investor at Georgian. They will break down Georgian’s latest thesis area: Product-led Purpose. 

Simply put, Product-led Purpose is our view that the next generation of market-leading technology companies will not only deliver superior economic value but also a quantifiable positive impact on societal challenges.

You’ll Hear About:

●  Georgian’s purpose and what it takes to get the whole team engaged.

●  Where the purpose came from and its ties to Georgian’s history.

●  How Georgian’s Purpose Report holds us accountable. 

●  Why Georgian launched a Product-led Purpose thesis and what that really means.

●  How a strong top-level executive focus on purpose can motivate and drive a company forward.

●  The main pillars of the Product-led Purpose thesis.

●  The natural tension between pushing technology and purpose.