What are the challenges hiring for an AI startups? How do you hire today, but be prepared for continously changing requirements of tomorrow? Or how do you convince the HR department of your talent and motivation?

If those questions have crossed your mint recently, than this episode with Tanja Zinkl, hiring for the successful Austrian AI company Kaleido, is for you!

References:

Tanja Zinkl : https://www.linkedin.com/in/tanja-zinkl-4aa647114/

Book : Data Teams - A unified Management Model for Successful Data-Focused-Teams by Jesse Anderson

Have you ever been excited to browse the other side of the world on google earth? Just to be disappointed by the poor quality of the 3d reconstructions, and the limited level of detail? 

The Graz based AI company blackshark.ai has you covered!

In todays interview, Stefan Habenschuss, leading machine learning at blackshark.ai is explaining

their massive scalable aerial image segmentation system that has been used to create a digital

twin earth with more than 1.5 Billion 3d building reconstructions with an astonishing level of detail.

References:

Stefan Habenschuss : https://www.linkedin.com/in/stefan-habenschuss-708459102/

A twin earth for the Microsoft Flight simulator : https://www.youtube.com/watch?v=ng-mGNqLe6M

Massively Scalable Aerial Image Segmentation for Virtual Sensor Simulation Environments : https://lnkd.in/dafgdvm (Available after a free registration at NVIDIA's GTC event platform) 

The field of AI and Machine learning is moving with an ever increasing pace, and for most small and medium companies that cannot afford their own research labs, keeping up new scientific papers and software frameworks is almost impossible.

Today on the show I interview Lukas Fischer who is the Research Manager of the Data Science branch of the Software Competence Center Hagenberg that is here to help companies achieve this difficult task. The center has the mission to enable the knowledge transfer from academia to private partners, so that they can stay ahead of the competition.

If you are interested to hear about the structure, challenges and career opportunities within an applied research institute at linking academia and private industry, then this episode is for you.

References:

Lukas Fischer: [email protected] , https://www.linkedin.com/in/lukas-fischer-3015245b/

Software Competence Center Hagenberg : https://www.scch.at/en/news

SCCH COMET Modul S3AI: https://www.s3ai.at (Research in the area of Secure and Save Shared Artificial Intelligence Systems)

H2020 Project Teaming.ai: https://www.teamingai-project.eu/ (Human-AI-Teaming-Plattform for the development and improvement of AI systems in manufacturing)

H2020 Project Cogniplant: https://www.cogniplant-h2020.eu/ (Platform for process improvements in industrial settings)

H2020 Project SERUMS: https://www.serums-h2020.org/ (Privacy preserving ML in the medical domain)

FFG Project in cooperation with the St. Anna children cancer research VISIOMICS: www.visiomics.at 

FFG COMET Funding: https://www.ffg.at/en/comet-competence-centers-excellent-technologies

SCCH SpinOff Sysparancy: https://www.sysparency.com/en/

On the show today, I have the pleasure to talk to Raphael Mitsch, currently working as a Senior Machine Learning Engineer at the Austrian AI consultancy enliteAI.

Are you curious to learn, what AI consultancy looks like in practice, and what skills are required to be successful as a consultant?

Or are you interested to hear about the challenges and opportunities of reinforcement learning in real world tasks?

If so, then this interview is for you!

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## Raphael Mitsch contact details

https://www.linkedin.com/in/raphaelmitsch/

[email protected]

github.com/rmitsch

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## Related links and references

https://github.com/enlite-ai/maze

https://www.enlite.ai/

Machine learning street talk #045 Microsoft's Platform for Reinforcement Learning (Bonsai): https://www.youtube.com/watch?v=zxs0wM-N1sQ

https://www.microsoft.com/en-us/ai/autonomous-systems-project-bonsai

https://gym.openai.com/

https://docs.ray.io/en/master/rllib.html

https://human-centered.ai/

On the show today, I have the pleasure to talk to Jillian Augustine.

Jillian is currently working as a Data Scientist in the Digital Excellence Team of the international paper and packaging manufacturer Mondi, but has received your Phd in Molecular Biology. On the show we are discussing Jillian experience working in academia and private industry. She is contrasting the mindset prominent on both sides, and what is needed to be successful, as well what industry can learn from academia, and vice versa.

In addition we briefly discuss different ways how domain experts and data scientists work together most efficiently, and how improvements of tooling and software might change this relationship in the future.

We end this episode, talking about diversity and inclusiveness. Jillian shares with us, what it means, and how it feels to be part of an underrepresented group. The importance of role models, and the intrinsic value of inclusiveness.

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Jillian Augustine (LinkedIn) - https://www.linkedin.com/in/jillianaugustine/

Personal homepage - https://www.jill.codes/

Woman Techmakers Vienna : From Test Tube to Data Lakes by Jillian Augustine - https://www.youtube.com/watch?v=VFFU282Fkn8&t=39s

The MDN Web Docs Accessibility guide - This covers a range of best practices when working with HTML, JavaScript and CSS : https://developer.mozilla.org/en-US/docs/Web/Accessibility

Moving into Data Science from Non-CS Academia - Women in Data Science CEE 2021 : https://www.youtube.com/watch?v=HcvFKknw508

Summary

Today on the show, we have Frank Fichtenmueller.

Frank is currently working as a Senior Solution architect, at Crayon's AI Center of Excellence; here in Vienna, where he is developing distributed systems at scale that apply the power of Machine Learning to solve real world problems and enable new business cases.

Frank has been in AI, for more than a decade now, going through many ups and downs. He has build and sold his own startup, started, managed and grew AI teams from he ground up, as well as organised and led the the AI efforts and strategies of complete companies.

I believe this episode is of great value for anyone that either is in a position to build a new a AI team at his/her company or that want to understand how the interests of an AI engineering team can collide with business needs.

In addition Frank shares his experience on what skills and expertise new comers in the field are often missing and what he would recommend to focus on (Spoiler, its less fancy data science or AI but more solid software development and DevOp skills).

We end the episode discussion a possible future of Data Science and where the market is heading, away from research and development towards the integration and coordination of Machine Learning services.

I really hope you enjoy this episode and can benefit from the experience and wisdom Frank is so happily sharing with us.

References

Frank Fichtenmueller: https://www.linkedin.com/in/frankfichtenmueller/

Crayon: https://www.crayon.com/at/

Summary

On this episode of the Austrian AI Podcast, we have the pleasure to interview Ivona Vlčková, a young Data Scientist working at the Viennese AI startup Mostly.ai. 

Ivona shares her experience working as a Data Scientists at a Startup with about 30 people and contrasts it with her experience working at an international company with thousands of employees.

We discuss her reasons to move to Vienna, and what Vienna has to offer and how it compares to other cities in attracting talent and companies in the AI sector.

Towards the end of the interview we discuss the topic of gender bias in Data Science and in Austrian companies in general.

It was a pleasure to host Ivona and a very interesting interview.

You can reach Ivona at [email protected], or via LinkedIn at https://www.linkedin.com/in/ivona-vl%C4%8Dkov%C3%A1-7175b8ab/ .

References

Mostly.ai: https://mostly.ai/

Gender Bias in Computer Science Degree at the TU-Vienna: https://www.tuwien.at/tu-wien/ueber-die-tuw/zahlen-und-fakten#c9039 

Book Recommendation: Jesse Anderson - Data Teams : https://www.datateams.io

On Differential Privacy: Differential Privacy:

A Primer for a Non-technical Audience, https://privacytools.seas.harvard.edu/files/privacytools/files/pedagogical-document-dp_new.pdf

Welcome to the Austrian AI Podcast!

I am your host, Manuel Pasieka and I am excited to share with you on this Podcast

I will bring onto the show, experts from academia and privat industry, hobbyists

I hope you will join me for this journey, and you are as excited about it as I am.