Episode highlights: 01:00 - Conversational AI for the future of marketing and sales, focus on the real estate industry. 04:00 - How Structurely works and what it solves. 06:50 - Benefits to businesses utilizing AI within their companies. 10:55 - The future of real estate by use of machine learning. 16:10 - Creating a more promising future for AI as a tool for positive outcomes. E.g. Zillow. 23:00 - Conversational AI's next big challenges. References: Nate's LinkedIn profile Nate's Twitter profile Structurely's Company Website ..read more

02:00 - Ada's performance, stories and metrics around. Size of the impact AI has in this space, as covered by Tradeshift. 05:35 - Working with AI/ML teams. 14:40 - Assessing how much data is needed for an AI project. 18:45 - Data risks. 24:25 - Is Agile good for AI teams? 27:30 - How much does UX matter in e-Invoicing and ML/Data projects? 36:35 - How can projects get derailed or fail? What should we watch out for. 40:05 - Funny fails. 41:50 - AI principles. References: Lloyd's Linkedin Profile Tradeshift's Ada technology Tradeshift's surpass of $1 trillion in transactions processed on thei ..read more

02:35 - Why hasn’t voice AI taken off already? 22:50 - Can we fulfil an end to end new purchase naturally? 32:20 - How can we resolve the disambiguation problem in NLU? 37:20 - Context and memory perspectives. 43:20 - How do we make conversations natural? References: Dustin's VUX World Podcast Dustin's Linkedin profile Hannes' LinkedIn profile Speechly's Twitter profile Speechly product search and checkout demo Speechly's Interspeech Research Paper 2021 ..read more

01:15 - How does NLP work? 04:05 - How do Transformer-based NLP models work? 08:20 - How to look at unstructured data to take advantage of it more. 12:00 - How to leverage ML to bring more to unstructured data? 15:25 - Approach for low resources languages. 23:25 - Word embeddings for common reasoning needs. 26:55 - Techniques to follow to improve error and ambiguity in training data or for a model in general. 30:10 - Are GPTs leading effort in the field in a wrong direction? 34:15 -  Is DeepLearning the end of AI? 37:20 - What are some good NLP metrics to watch? 42:05 - How do we get pas ..read more

12:50 - Is the Turing test still relevant? 21:30 - Why it's important to use methodologies in AI projects and what are some best practices out there fit for AI projects. 28:00 - Falsehoods of methodologies in AI projects. 35:00 - Is Agile a good framework for AI/ML projects/products? 40:10 - How can projects get derailed or fail if you don't have a plan in place. 44:20 - The best compliment one can get after building an AI project or system. 47:25 - Is DL the end of AI? References: CPMAI methodology Cognilytica's Voice Assistant Benchmark 1.0 and 2.0  AI Today podcast show with Alexand ..read more

2:10 - Using AI to augment and reshape creativity in a modern world. Psychological creativity and story creativity - can an AI model help AI music artists, today, get off their creative blocks? 12:15 - Attempt to define ‘good’ music, using a cognitive music literature background. 17:00 - Are we better or worse off, for AI in audio/music? Is it sustainable for the effort input and cost, impact and efficiency output? 22:35 - ‘Deep Nostalgia” from myheritage initiative, and GPT-J - looking for strengths in the two approaches. 29:25 - The Sound of AI community - a HuggingFace version for audio? 3 ..read more

1:50 - Using AI for the environment 6:55 - AI spices for agriculture 12:15 - AI in outdoor uses 15:15 - Green AI in Seekar's work 22:15 - Training AI models for a green AI approach 27:10 - Seekar in the medical space, and covid19 opportunities 39:15 - NLP tradeoffs and takeaways 43:10 - Similarities in practicing jiu-jitsu and AI References: Building AI models to be greener, and Seekar's Research Gate paper. This paper gives more insight into how Seekar was able to compress a large AI model down to a small enough size without compromising accuracy or performance. COVID-AI app from AppStore ..read more

01:25 - Do NLP models need someone that is not completely monolingual? 05:20 - Types of NLP  in marketing and/or e-commerce. 11:30 - Challenges in the e-commerce space: Behavioural data gathered by cookies has disappeared. 16:00 - Every 40 seconds, our attention breaks. Is that fact taken into account in NLP modeling for personalization? 18:20 - Models like GPT-3 open a whole new commercialization avenue in the marketing world, specifically for content creation. Impact of the wave. 21:50 - Is it fair to use an AI model for IP and content in such a way you influence millions of users on a ..read more

01:35 - Why did you decide to continue bootstrapping and decided to not opt for an investment. 06:50 - In the age of the million dollar supremacy how much money is a VC ready to invest. 08:56 Open source AI, good or bad idea? - VC and deep tech founder perspective. 14:15 - What’s the ideal shareholder split? 20:40 - Should one opt for Europe instead of Silicon Valley to raise capital faster? 23:10 - Effects of the pandemic on the deep tech investment space. 29:10 - Do VCs run their due diligence in their investment process + should VCs start considering checking reddit channels from now on? 3 ..read more

02:43 - Motivation behind building a scaled MOOC AI course 06:40 - Effort behind an AI course to educate 1% of EU citizens 10:45 - Finland's heritage in education, and AI takeaways for course takers 20:55 - AI Challenge, or how are companies joining the AI education movement 25:45 - Digital spending priority: digital skills & education OR upgrading our health systems - Opinion 30:13 - Feels of a creator after building a popular AI course 36:55 - Ethics of AI course, and Elements of AI new chapters exploration References: Elements of AI Romania Elements of AI global version  EU loca ..read more