lessons from the early days at uber and advice for founders

We’re excited to launch a new EIR program for data science founders in partnership with Rackhouse Ventures, founded by Kevin Novak. Learn more about the program: https://www.villageglobal.vc/rackhouse-village-global-eir-program

Kevin Novak (@novakkm), an early Uber employee, was instrumental in developing their data science program and was the creator of surge pricing.

Highlights:

– Kevin, originally a nuclear physicist, applied his analytical skills to develop Uber’s first surge pricing model in three weeks—a task that would typically take six months in academia.

– He says that founders shouldn’t wait until they have plenty of data to make decisions — instead, start with first principles thinking while also building a virtuous data cycle by ensuring you are collecting data that will inform future decisions.

– He comments that AI might be “overhyped on average” at the moment. The first breakthrough product is essentially an API, which has led to incumbents responding more quickly and more aggressively. Kevin argues that if you are founding a generative AI company, you are effectively making the claim that incumbents won’t be able to respond and implement an LLM themselves.

– Kevin cautions founders not to fall in love with any one idea too early. It’s better to hedge your bets and experiment with one or two. Through trial and error, you can eventually decide on one idea that has the potential to be a strong business. 

– For the Village Global-Rackhouse EIR program, we’re looking for founders with deep passion for founding a company. We don’t require you to have your idea and team established. 

Thanks for listening — if you like what you hear, please review us on your favorite podcast platform. 

Check us out on the web at villageglobal.vc or get in touch with us on Twitter @villageglobal.

generative ai for healthcare – with dr. dan elton of mass ge

Today’s guest is Dr. Dan Elton, a Data Scientist at the Mass General Brigham Data Science Office. He’s also a fellow at the Foresight Institute and previously served as a staff scientist at the National Institutes of Health. He joins Emerj Senior Editor Matthew DeMello on today’s show to talk about promising AI use cases in healthcare, including use cases in radiology, compliance, and medical record generation, search, and summarization. Later, the two discuss how foundational models will transform how AI is used in radiology. To discover more AI use cases, best practice guides, white papers, frameworks, and more, join Emerj Plus at emerj.com/p1.

from prescriptive to conversational genai in retail – with m

Today’s guest is Michael Tambe, Head of Data Science for Amazon Advertising Field Sales. Mike has led data science efforts in sales and marketing and leading edge companies like Amazon Ads and LinkedIn. Through these experiences he’s become an advocate of enterprises building a “data driven go to market engine.” He joins Emerj Senior Editor Matthew DeMello on today’s podcast to talk about what that means, along with the challenges and possibilities of new emerging AI capabilities. If you’ve enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!

#412 veit brucker | head of dach @asana und bjorn sjut | co-

“Technologie war einfach nur ein Mittel, um Menschen zu berühren und eine veränderte Arbeitsweise einzuführen.”

Unser heutiger Gast hat an der Universität Duisburg-Essen BWL mit den Schwerpunkten Wirtschaftsinformatik und Marketing studiert und mit einem Diplom-Kaufmann abgeschlossen. Nach leitenden Positionen im Vertrieb und Marketing bei Unternehmen wie Salesforce, Zuora, Snowflake, Siemens und Oracle ist er seit April 2023 als Head of DACH bei Asana. Sein Auftrag dort ist es, das Wachstum in der Region vorantreiben. Zu seinem Einstieg bei ASANA lies er sich in der Pressemitteilung wie folgt zitieren: “My role has always been to operate at the intersection of technology, culture, and change of business model, and Asana’s mission to enable the world’s teams to work together effortlessly aligns closely with this.” Doch unser Gast kommt nicht alleine. Mitgebracht hat er einen seiner Kunden. Er ist einer führenden deutschen Experten im Online-Marketing und wahrscheinlich der führende deutsche Experte im B-to-B Online-Marketing, er ist ein guter Freund und er ist Co-Founder von finc3 und Bizmut die seit Kurzem als Front Row firmieren.

Seit fast 7 Jahren beschäftigen wir uns nun schon mit der Frage, wie Arbeit den Menschen stärkt – statt ihn zu schwächen. In über 400 Folgen haben wir uns mit über 500 Menschen darüber unterhalten, was sich für sie geändert hat und was sich weiter ändern muss. Wir sind uns ganz sicher, dass es gerade jetzt wichtig ist. Denn die Idee von “New Work” wurde während einer echten Krise entwickelt. Welche Rolle spielt Technologie für eine gute Zusammenarbeit ganz allgemein? Und wie kann Software ganz konkret dabei helfen? Wir suchen nach Methoden, Vorbildern, Erfahrungen, Tools und Ideen, die uns dem Kern von New Work näher bringen! Darüber hinaus beschäftigt uns von Anfang an die Frage, ob wirklich alle Menschen das finden und leben können, was sie im Innersten wirklich, wirklich wollen. Ihr seid bei On the Way to New Work – heute mit Veit Brücker und Björn Sjut.

Hier findet ihr alle Links zum Podcast und unseren aktuellen Werbepartnern

749: data science for clean energy, with emily pastewka

Data science for clean energy takes center stage as Emily Pastewka from Palmetto joins Jon Krohn this week, exploring innovative paths to a sustainable future. This episode covers the impact of AI on smart energy choices, the creation of a smart grid, and the wide array of professionals required to bring cleantech data solutions to life.

This episode is brought to you by Prophets of AI (https://prophetsofai.com), the leading agency for AI experts. Interested in sponsoring a SuperDataScience Podcast episode? Visit passionfroot.me/superdatascience for sponsorship information.

In this episode you will learn:
• Emily on her Master’s in Deep Learning [08:20]
• Using AI to solve clean energy challenges at Palmetto [17:22]
• The different roles needed to solve cleantech problems [27:33]
• How econometrics impacts consumer decision-making [38:56]
• How Emily manages high-performing teams [56:30]
• The tools and technologies that drive small teams [1:06:58]

Additional materials: www.superdatascience.com/749

745: 2024 data science trend predictions

2024 data science trends take the spotlight in this special episode, where Jon joins Sadie St. Lawrence to analyze last year’s predictions and delve into the emerging technologies reshaping the field. From AI hardware accelerators to the transformative role of large language models, this episode is a treasure trove of insights for anyone interested in the future of data science.

This episode is brought to you by CloudWolf (www.cloudwolf.com/sds), the Cloud Skills platform. Interested in sponsoring a SuperDataScience Podcast episode? Visit https://passionfroot.me/superdatascience for sponsorship information.

In this episode you will learn:
• Reviewing predictions for 2023 [05:56]
• Sadie’s trend predictions for 2024 [20:49]
– 1: Hardware evolution [21:17]
– 2: LLMOS [35:30]
– 3: Slow-thinking model [48:18]
– 4: Tool consolidation [54:46]
– 5: Workforce Upheaval [58:06]
• Jon’s predictions [1:06:26]
– 1: AI bubble bursting [1:08:11]
– 2: Breakthroughs in Edge AI [1:12:22]
• Sadie on her productivity planner [1:17:50]

Additional materials: www.superdatascience.com/745

building trust in data science in life sciences – with bikal

Today’s guest is Bikalpa Neupane, Head of Artificial Intelligence and Natural Language Processing at Takeda. He joins us on today’s program to discuss how siloed data and trust in data science processes are among the biggest challenges facing life sciences leaders and the promise of new use cases and generative AI tools in confronting those challenges. If you’ve enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!

s3 | ep 50 | the seven sins of data transformation with jose

In Episode 50, of Season 3, of Driven by Data: The Podcast, Kyle Winterbottom is joined by Joseph George, CEO at Dufrain, where they discuss the seven sins of data transformation, which includes;

  • The differences between being an employee in a big corporate to running a business
  • The realities of the Data Science hype cycle in 2017/18
  • Why the good work is only done in pockets and silos
  • Research that suggests that only 27% of organisations are ready to achieve benefits from AI
  • Why they commissioned their ‘State of Data’ Report and some of the key findings
  • Why most organisations believe they’re significantly more data mature than they actually are
  • Why data is important but not urgent
  • How most organisations can’t tie their D&A work to any increase in profit /revenue
  • The reality of how organisations are still using data within an organisation
  • How organisations are suffering from the “streetlight effect”
  • Why most data and analytics projects still don’t deliver the desired benefits
  • How most of the blockers are non-technical
  • The seven sins of data transformation
  • Why data is an afterthought in most transformation programmes
  • The lack of good programme/project management on most data and analytics initiatives
  • The importance of understanding what success and ‘completed’ is for different stakeholders
  • Why many agile projects aren’t actually agile
  • The three lenses of collaboration and why the lack of it negatively impacts many D&A projects
  • Why everyone needs to think and act commercially and speak in business language
  • Why it all ties back to revenue
  • Why we all have to look in the mirror
  • The importance of being able to articulate the benefit of any data initiative
  • Why the CIO is being chosen over the CDO for having responsibility for AI

You can find The State of Data Report here; https://www.dufrain.co.uk/

ai today podcast: ai glossary series data science, data sc

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer delve into the diverse roles and concepts within the data universe: Data Science, Data Scientist, Citizen Data Scientist/Citizen Developer, and Data Custodian.

Data Science isn’t just a buzzword; it’s the art of transforming raw data into meaningful insights. And Data Scientists may be the sexiest job of the 21st Century, but do you know what they do? These wield algorithms and statistical models to extract pearls of wisdom from the data ocean. Or as we like to say “extracting information needles from data haystacks”.

We also go over what a data custodian is and how they are responsible for the safe storage, transfer, and use of data. The data custodian is not a data owner but serves as an administrative role over the data.

Join us on this episode as we unravel these roles, discussing their significance, responsibilities, and impact in today’s data-driven world.

Show Notes:

#27 nach ganz oben – war for talents (mit david dobele von

„Was willst du nach dem Abi machen?“ „BWL studieren.“

„Warum?!“ „Keine Ahnung, machen doch alle.“

Für wenige Studiengänge gibt es so viele Klischees wie für „die BWLer“.

Aber es gibt natürlich dabei eine sehr große Bandbreite zwischen den ideenlosen Langzeitstudenten und den hoch-ambitionierten High Potentials.

Um letzte buhlt die gesamte Finance Szene, denn auch hier herrscht ein Fachkräfte Mangel. Grund genug, dem von beiden Seiten auf den Grund zu gehen.

Das heißt für Studenten: Wie muss ich mich aufstellen, um bei den Top Banken und Beratern einen Platz zu ergattern.

Und für die Recruiter: Wie kann ich die Spreu vom Weizen trennen und die High Potentials zu mir locken.

Unser Gast in dieser Episode von 🤝𝘾𝙡𝙤𝙨𝙚 𝙏𝙝𝙚 𝘿𝙚𝙖𝙡🤝 ist BWL-Influencer und Co-Founder der Finance Karriere-Plattform Pumpkincareers und kennt beide Seiten nur allzu gut.

Mit David Döbele diskutiere ich,

• wie die aktuelle Lage im War for Talents ist,

• wie sich Recruiter aufstellen müssen um attraktiv zu sein und Mitarbeiter zu binden,

• ob Studenten einen strukturierten Karriereplan brauchen,

• wie der Einstieg bei den großen Häusern gelingt,

• und vieles mehr…

Viel Spaß beim Hören!


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