Season 2, Episode 2B
AI & The New Dimension of Innovation++:
Demos About Ai’s Real Impact on Future Change & Innovation
A webcast presented by the global innovation practice Futureproofing : Next (futureproofingnext.com).
You hopefully know by now that AI is already a big thing, and only getting bigger. We’re now going to peer inside the AI treasure chest and tell you why and how.
Join us for our first AI-specific Futureproofing Now webcast & podcast, where we provide some of the best practical takes on why, how and when AI will emerge as a force in many industries with “AI & the New Dimension of Innovation++” and how the very nature of change and transforming your business surrenders to AI’s advancement.
In the back half of our doubleheader, our twelvth episode of Futureproofing Now, profiles four experts and their compnaies that bring AI-to-life through hands-on demonstrations on how their AI enterprises & platforms work.
From a change agent’;s perspectives we’ll go through:
- why these AI companies and tools were created?
- the moving parts of technology that makes it all possible
- who’s it for?
- how does it make business bolder, bigger, easier, quicker or simpler?
- special features
- what’s next
Sean Moffitt & Andrea Kates, Co-Founders, Futureproofing : Next
- Kevin Surace, Chairman & CTO, Appvance.ai
- Christian Lawaetz Halvorsen, Chief Experience Officer, Valuer,ai
- Clarice Wong, Machine Learning Support Engineer, Labelbox
- Jonathan Eisenzopf, Founder & CTO, Discourse.ai
What you’ll learn:
- Table stakes – what is AI? what types exist?
- What are its underpinnings? key benefits and key watchouts?
- The top 10 applications of AI ranked and why each received their ranking
- A timeline when you are no longer going to be the early adopter of AI
- Some practical considerations implementing AI at scale
- A conversation with four leading AI experts implementing AI with customers & brands, talent & the workplace, change & innovation and transformation & process
- Demonstrations of four leading AI companies – Appvance, Valuer, Labelbox, Discourse
January 28th, 2020
Futureproofing Now Webcast Video
Futureproofing Now Podcast Audio
Hosts & Guests
Christian Lawaetz Halvorsen
Futureproofing Now Hosts:
About This Episode
0:00 Introduction of Topic, Webinar and Panel – A.I. our most requested topic from a previous F:N poll
1:05 Support for the Topic – AI real life importance – #1 technology of the decade
4:56 Top Ten AI Applications – ranked and impact beyond automation
6:10 Appvance. ai with Kevin Surace –
- Appvance – the Company: first AI-test-driven automation software launched in 2017,
- Benefit – augmented intelligence to free people up for other work, software is getting more complex, large company has 15,000 applications that run themselves, you can’t just add more people to test bugs on software,
- Friction – difference between high level management change interest and low level staffing displacement concern
- Demonstration & process – Appvance demonstration & benefits, 95% of QA budgets are people-based, 5 levels of machine learning autonomy, 70% of the world is at level 0 – manual testing, 100,000x faster than Selenium scripts, benefits accrue dramatically at Level 4 and 5, 19 machine learning methods applied, process – blueprint, production flow regression and productivity improvement
- Takeaway and watchout: augmented speed and value, AI as a human acceptance problem – trust the machine, please!
21:30 Valuer.ai with Christian Lawaetz Halvorsen –
- Valuer – the Company : hard to analyze and use a lot of data that exists on startups and solutions in corporate innovation – use a machine larning engine room to solve challenge
- Benefit – provide a focus and outputs to solutions search, objective lens, watering hole and middle point to the “Tinder” to the startup community, eanble startups and corporations to work together
- Friction – hard to analyze data and developments are moving so quickly
- Demonstration and benefits – 30-70 parameters and half-million qualified companies, process – data collection, data processing, clustering & radar vectors, voting and readjusted vector, radar projections, best fit, platform delivery, benefits – strength in refinement of data, pattern matching and better fit results
- Takeaway and watchout – makes the backyard much bigger for working with startups, better sync with matches (10-25 matches per search), strong real-life application, save time & energy for both sides – corporation & startup
37:20 Labelbox with Clarice Wong
- Labelbox – the Company : giving humans a better way to input & manage data, efficiency of data labelling & translation, scaled annotation of training data into software
- Benefit – cost & time, difference – human loop but software platform, transparency & customization
- Friction – all-consuming time of working on tools and managing them takes away from the actual application use and results
- Demonstration and benefits – group access to training data, datasets- collection of raw data, previous history and project workflows, possibility of programmatic workflow, label editor, segmentation,
- Takeaway and watchout – benchmark results, threshold scores for labellers – results improve over time, companies should focus on painting solutions on their paintbrushes
50:25 Discourse.ai with Jonathan Eisenzopf –
- Discourse – the Company : background in customer service, marketing & sales, how can I serve customers better with data from chatbots, texts or phone calls
- Benefit – build better bots faster, drive better customer servcie & experience
- Friction – automatically labelling conversational data, filter based on customer goal or specific terms
- Demonstration and benefits – real time ingestion of data inputs, dominant paths and steps, 8 different machine learning models, cost to develop, time, resources, ongoing cost savings, more capacity & unique flows
- Takeaway and watchout – change behaviour and much better customer experience, easier capture of tribal knowledge, need to ensure data can be aggregated and cross-channel
1:03:35 Round the Horn : AI Future Ahas – mining data effectively to capture – don’t have to start from scratch, focus on data amangamnet & collaboration vs the late stage complex algorithms, build a continuous learning pattern for clients, large companies should not be scared of this field – have reasonable POCs and realize benefits over the course of months and months, spirit of experinentation, ensuring data accuracy through AI, increasingly sophisticated things around AI are still to happen
1:07:30 Closeout and where to from here, #FN99 Chamgemakers’ bookshelf and upcoming webcasts
Our F:N Expert Panelists:
Chairman & CTO, Appvance.ai
Kevin Surace is a Silicon Valley innovator, serial entrepreneur, CEO, TV personality and EDUTAINER and has keynoted hundreds of events, from INC5000 to TED to the US Congress. He was INC Magazines’ Entrepreneur of the Year, a CNBC top Innovator of the Decade, World Economic Forum Tech Pioneer, Chair of Silicon Valley Forum, Planet Forward Innovator of the Year nominee, featured for 5 years on TechTV’s Silicon Spin, and inducted into RIT’s Innovation Hall of Fame. While he has a technical background with 85 worldwide patents, he is known as a very dynamic speaker who is a true entertainer that is funny, excites people, educates & energizes audiences to action.
Mr. Surace led pioneering work on the first cellular data smartphone (AirCommunicator), the first plastic multichip semiconductor packages, the first human-like AI virtual assistant (Portico), soundproof drywall, high R-value windows, AI-driven building management technology, AI-driven QA automation, and the window/energy retrofits of the Empire State Building and NY Stock Exchange. He is also an accomplished music director, conductor, producer, and percussionist, with over 1000 performances.
Kevin’s most requested talks include AI and Automation…It’s impact on your life and your company, Bringing Silicon-Valley Disruptive Innovation to Your Organization, Social Media’s Impact and Digital Transformation.
Christian Lawaetz Halvorsen
Chief Experience Officer, Valuer.ai
As CXO for Valuer.ai, Christian is responsible for coordinating overall customer experience, delivery, service and operations. His polygamous approach to knowledge results in an odd but useful skillset, some of which include: product innovation, supply chain management, whisky production, machine learning, fundamental understanding of the cosmos, skiing, programming in python, vexillology, and close-up magic.
Christian is a value-creating engineer working with network economies and platforms, and uses most of what he knows to increase his horizons on a daily basis.
Machine Learning Support Engineer, Labelbox
Clarice is a Machine Learning Support Engineer with a Bachelor’s degree in Mathematics and Computer Science from UC Davis.
She enjoys working on problems which give new perspectives; at Labelbox, this means seeing the platform through the eyes of users, and helping them optimize Labelbox for their specific ML goals.
In her free time, you might find her exploring (and probably critiquing) a new novel or watching Frasier.
Founder & CTO, Discourse.ai
Jonathan is passionate about teaching computers to have conversations with a human based n call center data for many years. He’s discovered how to train conversational bots to not be rude and to have useful conversations about defined topics. He is working with a select list of large enterprises to prove out its general usefulness across industries, by using new NLU and NLG techniques that implement universal conversational heuristics and graph theory combined with machine learning algorithms that enable conversational agents to approximate a synthetic “theory of mind”. He’s blended technology based on decades of research in the fields of Linguistics, Cognitive, Neuroscience, and Psychology that have not been implemented into a conversational bot framework.
His life motto: Think differently, ask hard questions, blaze new paths, fail quickly, adapt often, never tire, keep learning, don’t fail alone, be data driven, beauty in simplicity.
Jonathan has co-authored and been heavily involved in various standards and languages such as RSS, Perl, and VoiceXML and currently utilizing technologies including NLP, machine learning, Spark, Redis, neural networks, and Hadoop in languages ranging from R, Julia, Scala, Perl, Node.js, Max, and Python. Visualization technologies.
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We’re hungry to do work with passionate, driven people. The future is unwritten, let’s bring some future chapters to life.
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