Sora: Video-KI von OpenAI erreicht Hollywood-Niveau

Neue Video-KI: Dieser Screenshot eines durch OpenAI Sora generierten Videos zeigt eine lebendige Szene in einer Straße, die an Tokio erinnert – komplett erschaffen aus einem einfachen Textprompt.
Neue Video-KI: Dieser Screenshot eines durch OpenAI Sora generierten Videos zeigt eine lebendige Szene in einer Straße, die an Tokio erinnert – komplett erschaffen aus einem einfachen Textprompt.

Die künstliche Intelligenz (KI) hat einen neuen Meilenstein erreicht: OpenAI stellt mit Sora ein generatives KI-Modell vor, das die Videoproduktion grundlegend verändern könnte. Diese fortschrittliche Video-KI kann aus einfachen Textanweisungen innerhalb von Sekunden hochdetaillierte, 1-Minute-lange Videos erzeugen, die Hollywood-Niveau erreichen. Die Implikationen dieses Modells für die Content Creation sind immens und könnten die Landschaft der digitalen Medien nachhaltig prägen.

Ein tiefgehender Blick auf Sora, die Video-KI von OpenAI

Sora, als neuestes Mitglied der OpenAI-Familie, repräsentiert eine Spitzenleistung in der Entwicklung von Video-KI-Modellen. Es kann Szenen mit hoher Detailtreue, komplexer Kamerabewegung und Charakteren, die lebendige Emotionen zeigen, generieren. Die Fähigkeit von Sora, aus Textbeschreibungen solch komplexe Videos zu erstellen, markiert einen signifikanten Fortschritt in der KI-gestützten Content Creation.

Die Herausforderungen und Potenziale von OpenAI’s Sora

Mit der Einführung von Sora erwachsen auch neue Herausforderungen, insbesondere im Bereich der Sicherheit und Ethik der generierten Inhalte. OpenAI ist sich dieser Probleme bewusst und arbeitet an Lösungen wie einzigartigen Wasserzeichen, um die Authentizität und Herkunft von KI-generierten Videos zu kennzeichnen. Diese Bemühungen sind entscheidend, um das Potenzial der Video-KI verantwortungsvoll zu nutzen und gleichzeitig Missbrauch zu verhindern.

Video-KI: Eine neue Ära der Content Creation

Die Entwicklung von Sora durch OpenAI öffnet Content Creators neue Möglichkeiten, indem es den Zugang zur Videoproduktion demokratisiert und kreative Freiheiten erweitert. In meinem Buch KI für Content Creation diskutiere ich, wie solche Video-KI-Modelle neben anderen KI-Tools die Landschaft der digitalen Inhalte neu gestalten. Sora fügt dieser Diskussion eine wichtige Dimension hinzu und unterstreicht die Rolle der Künstlichen Intelligenz als unverzichtbares Instrument für die Zukunft der Content Creation.

Mit OpenAI Sora erstelltes Katzenvideo

Abschließende Gedanken zur Zukunft der Video-KI

Die Vorstellung von Sora durch OpenAI markiert nicht nur einen Meilenstein in der Evolution von KI-gestützter Videoproduktion, sondern wirft auch ein Licht auf den fortschreitenden Weg zur künstlichen allgemeinen Intelligenz (AGI). Während Sora bereits beeindruckende Fähigkeiten in der Erzeugung von Videos aus Textbefehlen demonstriert, legt es den Grundstein für zukünftige Entwicklungen, bei denen KI-Modelle zunehmend komplexe, kreative und intellektuelle Aufgaben übernehmen können, die bisher dem menschlichen Geist vorbehalten waren.

Wie ist euer Eindruck? Könnte die KI-Technologie hinter Sora die Videoproduktion transformieren? Schreibt gerne eure Ideen dazu auf LinkedIn, Instagram oder X (Twitter):

„Sora: Video-KI von OpenAI erreicht Hollywood-Niveau“ weiterlesen

Thank you Tableau and farewell!

Farewell to Tableau: A Reflective Goodbye - Alexander Loth with Tableau Data Rockstar t-shirt
Farewell to Tableau: A Reflective Goodbye – Alexander Loth

10 years ago, I started using Tableau.

4 years ago, I started working at Tableau.

Today is my last day with Tableau.

As I pen down my farewell to Tableau, it’s hard not to look back at the incredible journey that began 10 years ago. I reflect on a decade-long connection that began with using Tableau and culminated in four amazing years as an employee. This journey has shaped my career, leaving me filled with gratitude. Read about my 10-year blogging anniversary here.

These last four years have been the most inspiring of my career, what a ride it has been! It’s been a great opportunity and an amazing experience, joining this unique Seattle start-up as one of the first employees in Tableau’s Frankfurt office. Watching our DACH team grow to 120+ people is far more than I had imagined at the beginning, it is simply amazing!

As for my next phase, I’ll take on a strategist role at a leading cloud & AI company. I am excited to continue creating an impact in the digital age.

I’m very grateful to have worked alongside talented people both in Tableau and in our greater #datafam community — people who are brilliant and freakishly friendly. I am immensely grateful for the guidance of my mentors, Nate Vogel and Andy Cotgreave. Their wisdom and support have been instrumental in my growth at Tableau. I have many lifetime memories and made lots of great friends. I wish all of you at Tableau all the best for your next chapter, joining the Salesforce Ohana.

This farewell to Tableau is filled with gratitude, memories, and excitement for the future. Thank you, Tableau, for the incredible ride. So long, and thank you for everything!

— Alex

Watch my 4-years-in-2-minutes clip here:

Follow me on Twitter and LinkedIn for updates on my farewell to Tableau and new ventures.

#TC18 Wrap-up: Azure SQL Data Warehouse speeds up your Analysis

Benchmark: Microsoft Azure SQL Data Warehouse outperforms Amazon Redshift in TCP-H 30TB
Benchmark: Microsoft Azure SQL Data Warehouse outperforms Amazon Redshift in TCP-H 30TB

Slowly the dust settles after the impressive TC18. During my wrap-up, I remembered the data warehouse benchmarks of the Azure & Tableau session by James Rowland-Jones. Especially because my customers ask me about such performance metrics over and over again.

The first benchmark (graph above) shows how Microsoft Azure SQL Data Warehouse (aka. SQL DW) outperforms Amazon Redshift – in terms of performance and price. While the second benchmark shows further performance tests for Amazon Redshift, Snowflake, Azure, Presto, and Google Big Query:

Benchmark: Microsoft Azure SQL Data Warehouse Gen 2 vs. Amazon Redshift, Snowflake, Presto, Google Big Query
Benchmark: Microsoft Azure SQL Data Warehouse Gen 2 vs. Amazon Redshift, Snowflake, Presto, Google Big Query

Since James‘ session is already available on Tableau’s Youtube channel, feel free to watch the entire Azure & Tableau session:

#TC18 Sessions: Rock your Social Media Data with Tableau

My TC18 sessions in New Orleans: "Rock your Social Media Data with Tableau"
My TC18 sessions in New Orleans: „Rock your Social Media Data with Tableau“

Anyone can analyze basic social media data in a few steps. But once you’ve started diving into social analytics, how do you bring it to the next level? This session will cover strategies for scaling a social data program. You’ll learn skills such as how to directly connect to your social media data with a Web Data Connector, considerations for building scalable data sources, and tips for using metadata and calculations for more sophisticated analysis.

First session: Tues, 23 Oct,  12:30-1:30 (Location: MCCNO – L3 – 333)

Second session: Wed, 24 Oct, 10:15-11:15 (Location: MCCNO – L3 – 346)

Twitter Analysis #TC18 Dashboard featured as Tableau Public Viz of the Day
Twitter Analysis #TC18 Dashboard featured as Tableau Public Viz of the Day

Here are some key takeaways and links (i.e. additional resources) featured during my TC18 sessions to help you formulate your social media data program in order to build a stronger presence and retrieve powerful insights:

Prolog: Introducing data artist Noah

Step 1: Understand How to Succeed with Social Media

Apple has officially joined Instagram on 7th August 2017. This isn’t your average corporate account as the company doesn’t want to showcase its own products. Instead, Apple is going to share photos shot with an iPhone:

The Customer-Centric Data Strategy

Apple’s Instagram account is more an extension of the “Shot on iPhone” billboard ad campaign.

And there are plenty takeaways for every business:

  • Wrap your data around your customers, in order to create business value
  • Interact with your customer in a natural way
  • Understand your customer and customer behaviour better by analyzing social media data

Step 2: Define Your Social Objectives and KPIs

A previous record-holding tweet: In 2014, actor and talk show host Ellen DeGeneres took a selfie with a gaggle of celebrities while hosting the Oscars. That photo has 3.44 million retweets at the time of writing:

Social Objectives:

  • Define specific KPIs for social media platforms
  • KPI objectives need to be measurable
  • Metrics should be in line with the business goals

Step 3: Assemble Your KPIs

Brand Awareness and Reputation

Step 4: Connect Your Social Media with Tableau

Option 1 – Directly from the platform: Get data directly from Facebook, Twitter, YouTube, and more

Option 2 – Via web automation: Use a service like IFTTT to store data on Google Sheets

Option 3 – Via web data connector: Use Tableau’s web data connector, e.g. the Twitter Web Data Connector by Alex Ross (a.k.a. Tableau Junkie) -> http://bit.ly/tc18_twitter

Option 4 – Code your own solution: Use an API provided by the platform -> http://bit.ly/tc17_r_fetch

Option 5 – Via a third party platform: Get data from an integrated social media platform, such as Talkwalker -> http://bit.ly/tc17_talkwalker

Talkwalker - Via a Third Party Platform

Step 5: Apply some Tips to Level Up

Gather Historic Data

Step 6: Explore Social Media Listening

Social listening means that you look beyond your own content. E.g. Talkwalker offers AI for image recognition and ggregation for online/offline media: http://bit.ly/tc17_talkwalker

Step 7: Leverage Your Analytics Tool Chain

Use Your R and Python Skills

Demo/Tutorial: Let’s See this in Tableau!

How to analyse Social Media traffic with Google Analytics in Tableau (YouTube):

How to analyse Social Media data from Twitter in Tableau (YouTube):

Slide Set

The slides presented at Tableau Conference are also available on SlideShare.

Are you on Social Media?

Feel free to retweet/share:

[Update 25 Oct 2018]: Missed the sessions? Watch the recording online!

Social Media and the Customer-centric Data Strategy #data17 #resources

Social media marketing mix
Do you analyze your social media marketing mix? | Photo Credit: via Richard Goodwin

With over 3 billion active social media users, establishing an active presence on social media networks is becoming increasingly essential in getting your business front of your ideal audience. These days, more and more consumers are looking to engage, connect and communicate with their favorite brands on social media.

Adding social media to your customer-centric data strategy will help boost brand awareness, increase followership, drive traffic to your website and generate leads for your sales funnel. In 2017, no organization should be without a plan that actively places their brand on social media, and analyzes their social media data.

Once you’ve started diving into social media analytics, how do you bring it to the next level? This session covers a customer-centric data strategy for scaling a social media data program.

Here are the links (i.e. additional resources) featured during the session to help you formulate your social media data program in order to build a stronger presence and retrieve powerful insights:

The Data Opportunity

TC17 Social Media Slides: The Data Opportunity

Focus on relevant metrics for your strategy

TC17 Social Media Slides: Sentiment Analysis

How to get Social Media in Tableau?

TC17 Social Media Slides: 3rd Party Platform Talkwalker

Tips to Level Up

TC17 Social Media Slides: Unshorten URLs in Tableau with R

Tutorials and Slide Set

The slides and tutorials presented at Tableau Conference on Tour in Berlin are also available on SlideShare, and on YouTube in English and German.

English Tutorials

German Tutorials

Slide Set