Die Ära der generativen KI: Arbeit, Leben und Kunst im Umbruch? – Neue Folge von „Die Digitalisierung und Wir“

Unser Podcast-Thema: Generative KI - Arbeit, Leben und Kunst im Umbruch?
Unser Podcast-Thema: Generative KI – Arbeit, Leben und Kunst im Umbruch?

Schon lange hatten mein langjähriger Buddy Florian Ramseger und ich uns vorgenommen, einen deutschsprachigen Podcast zum Thema Digitalisierung und Gesellschaft zu machen. Immerhin sind 30.000 Follower auf LinkedIn keine schlechte Basis. Tatsächlich wird dieses wichtige Thema im deutschsprachigen Raum kaum diskutiert und wir wollen dazu beitragen, diese Lücke zu schließen. Für die kommenden Wochen haben wir einige spannende Episoden geplant – zum Teil mit spannenden Gästen. Wir freuen uns auf euer Feedback und wünschen viel Spaß beim Hören!

Unser Gast zum Thema Generative KI: Vladimir Alexeev

In unserer neuen Folge von „Digitalisierung und wir“ widmen wir uns dem Thema Generative KI und Kunst. Unser Gast ist Vladimir Alexeev, der sowohl als Digital Experience Specialist bei DB Schenker als auch als KI-Künstler und Forscher unter dem Pseudonym Merzmensch tätig ist. In dieser spannenden Episode sprechen wir über Vladimirs Buch über KI-Kunst, die Technologie hinter ChatGPT und werfen einen Blick in die Zukunft der KI-Entwicklung.

Einige der Fragen und Themen, die wir in dieser Episode behandeln, sind:

  • Wie Vladimir zur generativen KI kam und welche Rolle KI in der Kunst spielt.
  • Die Technologie hinter ChatGPT und wie Transformer-Netzwerke oder Large Language Models funktionieren.
  • Die rechtlichen und ethischen Fragen rund um KI-Kunst, wie Urheberrecht und kreative Tiefe.
  • Die Grenzen von Transformer-Netzwerken und wie sie unsere Arbeitswelt und unser tägliches Leben beeinflussen können.
  • Die Integration von KI in gängige Anwendungen wie Bing, Outlook, Word, Excel etc. und wie Google seine Produkte erweitern könnte.
  • Vladimirs Ansichten über die Rolle der KI in unserer Gesellschaft und wie sie als „Erweiterung“ des Menschen gesehen werden kann.

Die Grenzen der Kreativität verschieben

Diese Folge von „Die Digitalisierung und wir“ bietet einen faszinierenden Einblick in die Welt der generativen KI und der Kunst. Unser Gespräch mit Vladimir Alexeev zeigt, wie Künstler und Technologieexperten gemeinsam neue Wege beschreiten und die Grenzen der Kreativität erweitern. Seien Sie dabei, wenn wir die Chancen und Herausforderungen der KI-Entwicklung erkunden und diskutieren, wie sie unsere Zukunft gestalten wird.

Hören Sie die spannende Episode „Die Ära der generativen KI: Arbeit, Leben und Kunst im Umbruch?“ von „Die Digitalisierung und Wir“ und tauchen Sie ein in die Welt der KI-Kunst und -Technologie. Hier geht es direkt zum Podcast: www.digitalisierungundwir.de

„Die Ära der generativen KI: Arbeit, Leben und Kunst im Umbruch? – Neue Folge von „Die Digitalisierung und Wir““ weiterlesen

Die Digitalisierung und Wir: Der Podcast, der die digitale Welt erkundet

Die Digitalisierung und Wir: Podcast Cover
Die Digitalisierung und Wir: Der Technologie-Podcast mit Alex & Florian

Die Digitalisierung hat in den letzten Jahren immer mehr an Fahrt aufgenommen und wird in absehbarer Zeit weiterhin eine zentrale Rolle in unserem Leben spielen. Um dem rasanten Wandel in der Technologie gerecht zu werden und auf dem Laufenden zu bleiben, ist es wichtig, eine verlässliche Quelle für Informationen und Diskussionen zu haben. Genau das bieten wir mit unserem Podcast „Die Digitalisierung und Wir“.

„Die Digitalisierung und Wir“ ist ein wöchentlicher Podcast, der sich auf die Erkundung der digitalen Welt konzentriert. In jeder Folge sprechen wir mit Experten, Forschern und Vordenkern über die neuesten Trends und Innovationen im Bereich der Digitalisierung, Künstlichen Intelligenz und Technologie.

Einige der Themen, die wir in unserem Podcast behandeln, sind:

  • KI-Kunst und generative Modelle
  • Datenschutz und Cybersicherheit
  • Bildung und die Arbeitswelt im digitalen Zeitalter
  • Die Rolle von KI und maschinellem Lernen in verschiedenen Branchen
  • Die ethischen Fragen und gesellschaftlichen Auswirkungen der Digitalisierung

Unser Ziel ist es, eine Plattform für Wissensaustausch und Diskussionen rund um die Digitalisierung zu schaffen. Wir möchten nicht nur informieren, sondern auch inspirieren und dazu beitragen, ein Bewusstsein für die Chancen und Herausforderungen der digitalen Welt zu schaffen.

Werden Sie Teil unserer wachsenden Community und bleiben Sie stets auf dem Laufenden über die neuesten Entwicklungen in der Technologie. Hören Sie unseren Podcast, teilen Sie Ihre eigenen Ideen und Erfahrungen und seien Sie Teil der Diskussion rund um die Digitalisierung und ihre Auswirkungen auf unsere Gesellschaft.

Klicken Sie hier, um den Podcast zu abonnieren: www.digitalisierungundwir.de

 

AI Insights and Inspiration: My Story of Becoming a LinkedIn Top Voice with 30,000 Followers

Screenshot of Alexander Loth's LinkedIn profile, displaying the LinkedIn Top Voice badge, alongside the milestone achievement of 30,000 followers.
My LinkedIn profile, displaying the LinkedIn Top Voice badge, alongside the milestone achievement of 30,000 followers. Thank you very much!

I’m overjoyed to share an exciting milestone in my journey as a digital strategist and data scientist: my LinkedIn account has now reached a milestone of 30,000 followers! This achievement is more than just a number – it symbolizes a thriving community of enthusiasts passionate about data, AI, and digital transformation. The icing on the cake? Being recognized as a LinkedIn Top Voice in AI, an accolade that underscores my commitment to this fascinating field.

The surge in followers came on the heels of my inspiring ACM talk on Generative AI—a topic that captivates and challenges the norms of technology and creativity. This talk was more than a presentation of the work of our Microsoft AI For Good Lab; it was an invitation to explore the endless possibilities that AI brings to our world.

I cannot express enough gratitude for the overwhelming response to my book 📘 Decisively Digital  (➡️ Amazon). Each page was crafted with the intent to guide, enlighten, and inspire. Your support and feedback have been pivotal in its success.

What makes this journey truly remarkable is you – my followers, peers, and fellow enthusiasts. Our shared passion for data, AI, and digital technology has created a unique and vibrant community. Engaging with you, sharing insights, and learning from your perspectives has been one of the most rewarding aspects of my career.

One of the most exciting initiatives has been the #datamustread book club. Witnessing your engagement, the dynamic discussions, and how we are collectively uncovering the potential of data and analytics to shape our world is nothing short of inspiring.

As LinkedIn’s Top Voice in AI, I look forward to continuing our journey of discovery and discussion. Your thoughts, ideas and contributions are the lifeblood of this community. Let’s keep the momentum going and dive deeper into the realms of AI and digital innovation.

Thank you, each and every one of you, for your unwavering support and enthusiasm. Together, let’s take the road to the next 30,000 followers and beyond, making every step a leap toward a more informed, innovative, and inspired digital world.

The Rise of Generative AI: Revolutionizing Innovation and Enhancing Human Collaboration

Alexander Loth speaking at German Chapter of the Association for Computing Machinery (ACM) on March 24, 2023. Title of the presentation: "The Rise of Generative AI".
The Rise of Generative AI (photo by Bernd Vellguth)

Last week I had the pleasure of presenting a talk for the German Chapter of the Association for Computing Machinery (ACM). The session sparked lively discussions and elicited numerous thought-provoking questions from our engaged audience.

Following the talk, I was inspired by a conversation to leverage the power of GPT-4 and create an automatically generated summary of the Microsoft Teams transcript. This approach not only streamlines information sharing but also showcases the practical applications of advanced AI technology.

Below, I will share the key insights generated by GPT-4 and also include some captivating images from the event:


Decisively Digital: AI’s Impact on Society

In my talk, I drew inspiration from my book Decisively Digital, which discusses the impact of AI on society. I shared about the innovative projects underway at Microsoft’s AI for Good Lab. In light of GPT-4’s recent launch, I also highlighted our mission to leverage technology to benefit humanity.

Alexander Loth presents his book Decisively Digital, which also discusses Generative AI.
AI’s impact on society is discussed in Decisively Digital: From Creating a Culture to Designing Strategy. John Wiley & Sons. (photo by Gerhard Müller)

By harnessing Generative AI, we can stimulate the creation of innovative ideas and accelerate the pace of advancement. This cutting-edge technology is already transforming industries by streamlining drug development, expediting material design, and inspiring novel hypotheses. AI’s ability to identify patterns in vast datasets empowers humans to uncover insights that might have gone unnoticed.

Generative AI can Augment our Thinking

For instance, researchers have employed machine learning to predict chemical combinations with the potential to improve car batteries, ultimately identifying promising candidates for real-world testing. AI can efficiently sift through and analyze extensive information from diverse sources, filtering, grouping, and prioritizing relevant data. It can also generate knowledge graphs that reveal associations between seemingly unrelated data points, which can be invaluable for drug research, discovering novel therapies, and minimizing side effects.

„Now is the time to explore how Generative AI can augment our thinking and facilitate more meaningful interactions with others.“

Alexander Loth

At the AI for Good Lab, we are currently employing satellite imagery and generative AI models for damage assessment in Ukraine, with similar initiatives taking place in Turkey and Syria for earthquake relief. In the United States, our focus is on healthcare, specifically addressing discrepancies and imbalances through AI-driven analysis.

Our commitment to diversity and inclusion centers on fostering digital equality by expanding broadband access, facilitating high-speed internet availability, and promoting digital skills development. Additionally, we are dedicated to reducing carbon footprints and preserving biodiversity. For example, we collaborate with the NOAH organization to identify whales using AI technology and have developed an election propaganda index to expose the influence of fake news. Promising initial experiments using GPT-4 showcase its potential for fake news detection.

Alexander Loth: "We live in a rapidly changing world, facing big challenges."
„We live in a rapidly changing world, facing big challenges.“ (photo by Gerhard Müller)

ChatGPT will be Empowered to Perform Real-time Website Crawling

While ChatGPT currently cannot crawl websites directly, it is built upon a training set of crawled data up to September 2021. In the near future, the integration of plugins will empower ChatGPT to perform real-time website crawling, enhancing its ability to deliver relevant, up-to-date information, and sophisticated mathematics. This same training set serves as the foundation for the GPT-4 model.

GPT-4 demonstrates remarkable reasoning capabilities, while Bing Chat offers valuable references for verifying news stories. AI encompasses various machine learning algorithms, including computer vision, statistical classifications, and even software that can generate source code. A notable example is the Codex model, a derivative of GPT-3, which excels at efficiently generating source code.

Microsoft has a long-standing interest in AI and is dedicated to making it accessible to a wider audience. The company’s partnership with OpenAI primarily focuses on the democratization of AI models, such as GPT and DALL-E. We have already integrated GPT-3 into Power BI and are actively developing integrations for Copilot across various products, such as Outlook, PowerPoint, Excel, Word, and Teams. Microsoft Graph is a versatile tool for accessing XML-based objects in documents and generating results using GPT algorithms.

Hardware, particularly GPUs, has played a pivotal role in the development of GPT-3. For those interested in experimenting with Generative AI on a very technical level, I recommend Stable Diffusion, which is developed by LMU Munich. GPT-3’s emergence created a buzz, quickly amassing a vast user base and surpassing the growth of services like Uber and TikTok. Sustainability remains a crucial concern, and Microsoft is striving to achieve a CO2-positive status.

Generative AI Models have garnered Criticism due to their Dual-use Nature

Despite its potential, Generative AI models such as GPT-3 have also garnered criticism due to their dual-use nature and potential negative societal repercussions. Some concerns include the possibility of automated hacking, photo manipulation and the spread of fake news (➡️ deepfake disussion on LinkedIn). To ensure responsible AI development, numerous efforts are being undertaken to minimize reported biases in the GPT models. By actively working on refining algorithms and incorporating feedback from users and experts, developers can mitigate potential risks and promote a more ethical and inclusive AI ecosystem.

Moving forward, it is essential to maintain open dialogue and collaboration between AI developers, researchers, policymakers, and users. This collaborative approach will enable us to strike a balance between harnessing the immense potential of AI technologies like GPT and ensuring the protection of society from unintended negative consequences.

Alexander Loth discusses Microsoft's responsible AI principles: fairness, reliability and safety, privacy and security, and inclusiveness, underpinned by transparency and accountability, which also apply to Generative AI.
Microsoft‘s responsible AI principles: fairness, reliability & safety, privacy & security, and inclusiveness, underpinned by transparency and accountability. (photo by Gerhard Müller)

GPT-3.5 closely mimics human cognition. However, GPT-4 transcends its forerunner with its remarkable reasoning capabilities and contextual understanding. GPT models leverage tokens to establish and maintain the context of the text, ensuring coherent and relevant output. The GPT-4-32K model boasts an impressive capacity to handle 32,000 tokens, allowing it to process extensive amounts of text efficiently. To preserve the context and ensure the continuity of the generated text, GPT-4 employs various strategies that adapt to different tasks and content types.

GPT-4 Features a Robust Foundation in Common Sense Reasoning

One of GPT-4’s defining features is its robust foundation in common sense reasoning. This attribute significantly contributes to its heightened intelligence, enabling the AI model to generate output that is not only coherent but also demonstrates a deep understanding of the subject matter. As GPT-4 continues to evolve and refine its capabilities, it promises to revolutionize the field of artificial intelligence, expanding the horizons of what AI models can achieve and paving the way for future breakthroughs in the realm of generative AI.

Comparisons between GPT-4 and GPT-3 show the superior performance of the former in various tasks. Finally, I will present the results of my live Twitter poll asking the audience about the feasibility of achieving Artificial General Intelligence (AGI). Nearly half of the respondents are of the opinion that AGI is achievable within the next five years.

Alexander Loth discussing the results of the live Twitter survey: 47.8% predict the emergence of AGI is possible within the next 5 years
Results of the live Twitter survey: 47.8% predict the emergence of AGI is possible within the next 5 years (photo by Bernd Vellguth)

In the near future, advanced tools like ChatGPT will elucidate intricate relationships without requiring us to sift through countless websites and articles, further amplifying the transformative impact of Generative AI.

I appreciate the opportunity to share my insights at the German Chapter of the ACM.


The slides of my talk are available on ResearchGate.

Did you enjoy this GPT-generated Summary of my Talk?

Leveraging GPT-4 to generate a summary of my talk was an exciting experiment, and I have to admit, the results are impressive. GPT was able to provide a brief overview of the key takeaways from my talk.

Now, I would love to hear about your experiences with GPT. What are your experiences with GPT so far? Feel free to share your thoughts in the comments section of this Twitter thread or this LinkedIn post:

„The Rise of Generative AI: Revolutionizing Innovation and Enhancing Human Collaboration“ weiterlesen

GPT-4 Launches Today: The Rise of Generative AI from Neural Networks to DeepMind and OpenAI

OpenAI GPT-4 launch illustrated with Stable Diffusion (CC BY-SA 4.0)
OpenAI GPT-4 launch illustrated with Stable Diffusion (CC BY-SA 4.0)

With today’s launch of OpenAI’s GPT-4, the next generation of its Large Language Model (LLM), generative AI has entered a new era. This latest model is more advanced and multimodal, meaning GPT-4 can understand and generate responses based on image input as well as traditional text input (see GPT-4 launch livestream).

Generative AI has rapidly gained popularity and awareness in the last few months, making it crucial for businesses to evaluate and implement strategies across a wide range of industries, including e-commerce and healthcare. By automating tasks and creating personalized experiences for users, companies can increase efficiency and productivity in various areas of value creation. Despite being in development for decades, it’s high time for businesses to apply generative AI to their workflows and reap its benefits.

Before you dive into OpenAI GPT-4, let’s take a quick look back at the evolution of generative AI…

The history of generative AI begins in the late 1970s and early 1980s when researchers began developing neural networks that mimicked the structure of the human brain. The idea behind this technology was to assemble a set of neurons that could pass information from one to another with some basic logic, and together the network of neurons could perform complicated tasks. While minimal advances were made in the field, it remained largely dormant until 2010, when Google pioneered deep neural networks that added more data, hardware, and computing resources.

In 2011, Apple launched Siri, the first mass-market speech recognition application. In 2012, Google used the technology to identify cats in YouTube videos, finally reviving the field of neural networks and AI. Both Google and NVIDIA invested heavily in specialized hardware to support neural networks. In 2014, Google acquired DeepMind, which built neural networks for gaming. DeepMind built AlphaGo, which went on to defeat all the top Go players, a pivotal moment because it was one of the first industrial applications of generative AI, which uses computers to generate human-like candidate moves.

OpenAI was founded to democratize AI as a non-profit organization

In 2015, OpenAI was founded to democratize AI and was established as a non-profit organization. In 2019, OpenAI released GPT-2, a large-scale language model capable of producing human-like text. However, GPT-2 sparked controversy because it could produce fake news and disinformation, raising concerns about the ethics of generative AI.

In 2021, OpenAI launched DALL-E, a neural network that can create original, realistic images and art from textual description. It can combine concepts, attributes, and styles in novel ways. A year later, Midjourney was launched by the independent research lab Midjourney. Also in 2022, Stable Diffusion, an open-source machine learning model developed by LMU Munich, was released that can generate images from text, modify images based on text, or fill in details in low-resolution or low-detail images.

OpenAI launched ChatGPT in November 2022 as a fine-tuned version of the GPT-3.5 model. It was developed with a focus on enhancing the model’s ability to process natural language queries and generate relevant responses. The result is an AI-powered chatbot that can engage in meaningful conversations with users, providing information and assistance in real-time. One of the key advantages of ChatGPT is its ability to handle complex queries and provide accurate responses. The model has been trained on a vast corpus of data, allowing it to understand the nuances of natural language and provide contextually relevant responses.

Today’s launch of OpenAI GPT-4 marks a significant milestone in the evolution of generative AI!

This latest model, GPT-4, is capable of answering user queries via text and image input. The multimodal model demonstrates remarkable human-level performance on various professional and academic benchmarks, indicating the potential for widespread adoption and use. One of the most significant features of OpenAI GPT-4 is its ability to understand and process image inputs, providing users with a more interactive and engaging experience.

Users can now receive responses in the form of text output based on image inputs, which is a massive step forward in the evolution of AI. Depending on the model used, a request can use up to 32,768 tokens shared between prompt and completion, which is the equivalent of about 49 pages. If your prompt is 30,000 tokens, your completion can be a maximum of 2,768 tokens.

Token limitations of GPT models with real-world scenarios
Token limitations of GPT models with real-world scenarios

Bing has already integrated GPT-4 and offers both, chat and compose modes for users to interact with the model. With the integration of GPT-4, Bing has significantly enhanced its capabilities to provide users with more accurate and personalized search results, making it easier for them to find what they are looking for.

The disruptive potential of generative AI is enormous, particularly in the retail industry. The technology can create personalized product recommendations and content, and even generate leads, saving sales teams time and increasing productivity. However, the ethical implications of generative AI cannot be ignored, particularly in the creation of disinformation and fake news.

To sum up, generative AI is here to stay, and companies must evaluate and implement strategies swiftly. As generative AI technology advances, so do the ethical concerns surrounding its use. Therefore, it is critical for companies to proceed with caution and consider the potential consequences of implementing generative AI into their operations.

Are you already using generative AI for a more productive workflow?

What improvement do you expect from OpenAI GPT-4 in this regard? I look forward to reading your ideas in the comments to this LinkedIn post:

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