Generative AI and the authoritarian regimes

☕️ Greetings AI enthusiasts! It's Tuesday, September 12th. Welcome back to our daily dive into the AI landscape. We'll navigate the latest updates, trends, and insights from the AI and the business world. Let's begin!

🤖 Generative AI is a potential boon for authoritarian regimes. The West is busy debating the ethical implications, but the real danger lies in how autocrats could weaponize this tech for mass-scale propaganda. China and Russia are already investing heavily in AI to control public opinion. The US and its allies need to act fast, tightening export controls and investing in countermeasures, or risk enabling a new era of techno-authoritarianism.

Reference/Source: The Hill (Generative AI could be an authoritarian breakthrough in brainwashing)

🗞️ Today’s Highlights:

• LATEST NEWS & TRENDS — Report: Data centers guzzling enormous amounts of water to cool generative AI servers

• INDUSTRY | FUNCTION — Generative AI across airline operations

• RESOURCES — 6 Brilliant New Free Courses by Andrew Ng on Generative AI

• WORK — How generative AI is augmenting the engineering process

• AI TOOLS — SecondNature: Get your sales teams selling better & faster

• CHARTS — Top Of Mind. Generative AI hype or truly transformative?

🗞️ LATEST NEWS & TRENDS

1️⃣ When we think about the thirst for power in AI, we usually focus on electricity. Yet, the latest environmental reports from tech behemoths Microsoft and Google spotlight a lesser-known but equally critical resource: water. With Microsoft gulping down over 1.7 billion gallons in a year, and Google trailing closely behind, it's an environmental wake-up call. Shaolei Ren, an academic researcher, points out that as AI workloads increase, so does the drain on our water reservoirs. Analyst Holger Mueller suggests that while data centers do recycle water, the primary concern remains the non-recyclable energy consumption. Though companies aim for "water positivity," the journey is long and brimming with challenges.

Reference: (Report: Data centers guzzling enormous amounts of water to cool generative AI servers)

2️⃣ Navigating the M&A landscape with AI and Generative AI is like playing 4D chess. It's not just about due diligence anymore; it's about understanding the legal, ethical, and regulatory intricacies of AI tech. Think IP rights, data protection, and cyber threats. Oh, and let's not forget the looming EU AI Act and Switzerland's emerging focus on AI regulation. So, if you're an investor or dealmaker, you better have a team that's as diverse as the challenges you're about to face.

Reference: (Switzerland: Navigating Generative AI In M&A Transactions)

3️⃣ IBM is stepping up its game in the cutthroat AI arena with new generative AI models on its Watsonx platform, dubbed the Granite series. These models are shrouded in mystery but promise enterprise-quality data and specialized subsets for tasks like finance. IBM is also rolling out Tuning Studio, a tool for customizing AI models, and a synthetic data generator. Amidst financial pressures, IBM aims to be a transformation partner for businesses, offering a full suite of AI solutions from data strategy to governance.

Reference: (IBM rolls out new generative AI features and models)

4️⃣ Warner Music Central Europe has inked a groundbreaking deal with virtual influencer Noonoouri, releasing her AI-generated single "Dominoes." While Noonoouri's avatar is CGI-based, her singing voice is AI-produced. This marks a shift in the virtual influencer landscape, which has been traditionally CGI-centric. The move also raises questions about the future of virtual talent in the US, as generative AI tools become more accessible, potentially revolutionizing content creation and marketing strategies.

Reference: (How Generative AI will enable next-gen virtual influencers)

5️⃣ Generative AI is having its moment in the spotlight, but it's been evolving for over a decade. Fueled by open-source libraries like Tensorflow and PyTorch, advancements in neural networks, and hardware like GPUs, these models can now create synthetic data that mimics the real thing. They've gone from simple beginnings to complex architectures, like GANs and VAEs, and are now integral in various applications—from deepfakes to code generation. However, they're not without risks, such as producing misleading or inappropriate content. So, while the future looks promising, caution is advised.

Reference: (Lessons From a Decade of Generative AI)

🗞️ INDUSTRY | FUNCTION

Lufthansa's Digital Hangar is making strides in generative AI to enhance customer experience. CTO Christian Spannbauer reveals that the focus isn't just on tech but also on aligning it with internal regulations and culture. The AI is being trained to handle tasks from content creation to customer service. The real challenge? Ensuring data quality for accurate AI responses. Spannbauer envisions a future where AI will be a ubiquitous tool in Lufthansa's operations, from coding to meeting minutes, making life easier for both employees and customers.

Reference: (AI Insights: Generative AI across airline operations)

🗞️ RESOURCES

Andrew Ng's DeepLearning.AI has rolled out six new, free-to-access courses in collaboration with tech giants like Microsoft and Google. These bite-sized courses, ranging from one to two hours, cover everything from semantic search and finetuning large language models to building generative AI apps. Whether you're a Python novice or a deep learning pro, there's something for everyone. The courses aim to democratize AI literacy, making cutting-edge knowledge accessible and time-efficient.

Reference: (6 Brilliant New Free Courses by Andrew Ng on Generative AI)

The NExT-GPT ventures beyond the limitations of current Multimodal Large Language Models, introducing a game-changing any-to-any system. It’s not just about understanding different types of input; this AI juggernaut produces content in various modalities too. Through strategic tuning and ingenious architecture like MosIT, it brings us closer to truly human-like AI—bridging semantic comprehension across text, images, videos, and audio while keeping resource consumption in check. A future-forward move that’s rewriting the AI playbook.

Reference/Credit/Source: ArXiv (NExT-GPT: Any-to-Any Multimodal LLM)

🗞️ WORK

In this article by Siemens, Dr. Justin Hodges discusses the transformative power of generative AI in engineering and design. He introduces the concept of "inverse engineering," where AI starts with a set of requirements to arrive at optimized designs, a task nearly impossible for humans. Tools like Siemens' HEEDS facilitate this by aiding in design space exploration. Generative AI doesn't aim to replace humans but to augment their capabilities, enabling faster, more efficient design processes and fostering innovation in creating smarter, more sustainable products.

Reference: (How generative AI is augmenting the engineering process)

🗞️ AI TOOLS

🔧 SecondNature: Get your sales teams selling better & faster

🔧 DeepBrain AI Studio: AI-Powered text-to-video editor

🔧 aiXcoder: Intelligent programming robot. Help you develop efficiently Enjoy programming fun

🔧 Spinach: Spinach gives agile teams instant meeting summaries with decisions, actions, and ticket suggestions.

🔧 Runway Gen-2: Create videos in any style you can imagine with Text to Video generation. If you can imagine it, you can generate it.

Disclaimer: 1) The tool descriptions are from the company behind each tool/app. 2) Please read the site details thoroughly before using and/or acquiring any of the tools listed above. We have not tested these tools and we will not be liable for anything.

🗞️ CHARTS

👀 Top 10 Generative AI Trends in 2023

1. Hyper-Personalization

2. Conversational AI

3. AI for Scientific Research

4. Image Generators

5. Code & App Builders

6. Video Production

7. Generative Design

8. Speech Synthesis

9. Intelligent Process Automation

10. Generative Music

Source/Credit: Startus-Insights

👀 Since ChatGPT's debut, investor buzz around generative AI is skyrocketing. Experts like Sarah Guo and Gary Marcus weigh in on its capabilities and limitations. While GS economists see a productivity boost and potential gains for U.S. stocks, they caution about the risk of equity bubbles. The conversation also touches on hot investment spots in AI and the immediate risks investors should keep an eye on.

Reference/Source: Goldman Sachs (Top Of Mind. Generative AI hype or truly transformative?)

Disclaimer: The audio-visual content is courtesy of the source provided above.

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_{I'm not a newsletter expert so you might find my approach a tad different. In my daily dives into the world of AI, I handpick the latest gems, initially to support the AI projects that I’m working on. Realizing that these snippets might resonate with others, I thought, "Why not share this with my community and fellow AI enthusiasts?" I truly want this newsletter to be valuable to you so if there's anything on your mind—praises, critiques, or just a hello—please drop me a note. You can hit reply or shoot me a message directly at my email address: [email protected].}