AI Bytes Newsletter Issue #40

Welcome to this week’s AI Bytes, where we’re covering a range of exciting developments and critical conversations in AI. First, we explore how Adobe’s new AI-powered tools, showcased at Adobe MAX, are revolutionizing creative work, making it easier for designers and artists to innovate. Then, we dive into Tesla’s highly anticipated Cybercab robotaxi and its potential to reshape autonomous transportation. On the ethical front, we take a closer look at the limitations of machine learning models, discussing the risks of bias and errors in industries that rely heavily on AI. For those looking to boost productivity, our AI Tool of the Week is Gamma.app, a tool that helps users quickly generate visually stunning presentations. Lastly, we discuss the future of coding education in an AI-dominated world, questioning whether traditional coding skills will remain essential. Thank you for joining us again this week! Let’s get to it!

The Latest in AI

A Look into the Heart of AI

Featured Innovation
Maximizing Creativity: Adobe MAX Unveils RTX-Accelerated AI Tools for Next-Level Content Creation

This week's featured innovation spotlights major updates announced at the Adobe MAX creativity conference, highlighting AI-powered advancements integrated into Adobe Creative Cloud tools, such as Premiere Pro and After Effects, which are now RTX-accelerated. One of the most exciting features is the Generative Extend tool in Premiere Pro, powered by the Firefly Video Model. This allows seamless extension of video clips using generative AI, trained on commercially safe content, making content creation faster and more reliable for professionals.

In the 3D space, Adobe's Substance 3D Collection now boasts enhanced RTX-accelerated capabilities like ray tracing and AI-powered tools such as Text to Texture and Image to Texture. The new Substance 3D Viewer app, launched in open beta, bridges 3D and 2D design workflows by improving compatibility between design teams and providing real-time updates with tools like Photoshop. These innovations make 3D content creation smoother, while generative AI features expand design possibilities.

Additionally, the October NVIDIA Studio Driver release brings optimized performance for creative apps, including enhanced rendering and speed improvements for GPUs like the GeForce RTX 4090. Creators using these Adobe tools, paired with NVIDIA’s cutting-edge hardware, will experience faster workflows and higher-quality content production, all thanks to these AI-driven advancements.

Ethical Considerations & Real-World Impact 
The Fragility of AI: Why We Can’t Blindly Trust Machine Learning Models

AI models like the ones from Apple have hit a pretty embarrassing wall with basic tasks—things like simple math. Throw in a minor detail, something that wouldn’t trip up a kid, and suddenly these systems are spitting out bad answers. That’s a huge problem, especially when these models are getting hyped up for their “reasoning” skills and are already being put to work across big industries.

If an AI can't handle small tweaks in simple math, what happens when it's making real-world calls in finance, healthcare, or education? Picture this: a system trusted to diagnose someone, or approve a loan, can’t adjust to slightly different data. That’s not just a minor technical glitch—that’s a huge risk. People expect these tools to think like humans, but in reality, all they’re doing is recycling patterns they’ve seen before. And it gets worse when you consider ethical decisions, like deciding who gets a loan or who should be prioritized for treatment. AI’s not ready for that level of nuance.

As AI continues to integrate into critical areas of life, it’s essential that we recognize its limitations. Instead of treating these systems as flawless decision-makers, we need to approach them with caution, ensuring that human oversight remains a priority—especially when the stakes are high. Understanding what AI can and cannot do is key to using it responsibly.

AI Tool of the Week - Gamma.app

The Toolbox for using AI

We’ve been using gamma for some months and it just keeps getting better. Similar to how HeyGen dominates the AI video avatar space, gamma.app dominates gen AI presentations. Mike wrote an article all about getting going with gamma , you’ll be up and running in a few minutes, check it out below:

Rico's Roundup

Critical Insights and Curated Content from Rico

Skeptics Corner
Tesla’s Cybercab – Autonomy or Another Pipe Dream?

Elon Musk has never shied away from bold promises, and his latest unveiling—the Tesla Cybercab robotaxi—appears to follow the same pattern. At Tesla’s “We, Robot” event, Musk introduced the world to his vision of a future dominated by self-driving cars, free of steering wheels and pedals, and promising to revolutionize transportation. With doors that open like butterfly wings and a cabin designed for just two passengers, the Cybercab seems straight out of a sci-fi movie. But as we’ve seen many times before, hype doesn’t always translate into reality.

A History of Missed Deadlines and Unfulfilled Promises

Musk has long touted autonomous vehicles as the future, claiming they will be 10-20 times safer than human drivers. And if his predictions hold true, the Cybercab could reduce transportation costs to as little as 20 cents per mile—far below what we currently pay for public transit. The catch? The timeline for production keeps getting pushed back. Tesla claims the Cybercab will be available as early as 2026, though Musk himself admitted it might take until 2027. If Tesla’s track record is any indication, that estimate could easily slip further into the future.

Let’s not forget that Musk has been promising full autonomy since 2016, and here we are, eight years later, still waiting for a truly driverless Tesla that can navigate complex environments without a human behind the wheel. While other companies like Waymo and Cruise have made tangible progress, logging millions of miles in fully autonomous mode, Tesla is lagging behind. Its Full Self-Driving (FSD) system is still at Level 2 automation, requiring drivers to stay alert and ready to take control at all times—a far cry from the autonomy Musk envisions.

The Safety Question: A Risk We Can't Ignore

Musk’s claims of safety have not always matched reality. Earlier this year, a tragic incident involving Tesla’s FSD feature led to the death of a motorcyclist. Despite these serious incidents, Tesla continues to aggressively push its technology without fully addressing the safety concerns. The Cybercab’s futuristic design—lacking a steering wheel or pedals—means it will require approval from regulators before it can hit the roads. Given the safety record of Tesla’s current driver-assist systems, it’s fair to question whether the Cybercab is ready for the real world.

Federal safety regulators are already probing several major players in the autonomous vehicle space after a series of mishaps involving robotaxis. From traffic jams to minor accidents, these vehicles are far from foolproof, and Tesla’s Cybercab will be no exception. Can we trust a company with such a checkered history to safely deploy fully autonomous vehicles at scale? That’s a question regulators, and the public, need to carefully consider.

Hype vs. Reality

While the Cybercab may seem revolutionary, it’s important to remember that Tesla’s entire business model is built on Musk’s ability to sell big ideas—whether or not they’re immediately achievable. Tesla’s stock price often reflects faith in Musk’s vision rather than the company’s actual accomplishments. The Cybercab is part of Tesla’s broader push to transition from a car manufacturer to a company focused on robots and AI. The fact that Musk is now talking more about his Optimus robot—another highly ambitious project—than about the bread-and-butter of Tesla’s electric vehicles shows how much of Tesla’s future rests on speculative tech.

Musk is framing autonomous vehicles as massive time-savers, allowing passengers to reclaim hours spent commuting. But the idea that we’re just a few years away from fully reliable robotaxis that can operate without human intervention is overly optimistic at best, and misleading at worst. While companies like Waymo and Cruise are already testing fully autonomous vehicles in controlled environments, these systems are still far from foolproof. In the real world, they encounter numerous unpredictable challenges—something Tesla’s approach hasn’t proven it can handle.

Conclusion: Skepticism Is (Still) Warranted

Elon Musk’s Cybercab is yet another shiny new toy in Tesla’s lineup of futuristic promises. While it’s easy to get swept up in the hype of a driverless future, the reality is that we’re still years away from fully autonomous vehicles that are safe, reliable, and affordable. Musk’s lofty goals have always captured imaginations, but we should be cautious about treating them as inevitable outcomes. Tesla may yet surprise us, but for now, the Cybercab seems more like a vision of what could be rather than a glimpse of what’s just around the corner.

As with many of Musk’s ventures and many others, we’ll believe it when we see it. Until then, a healthy dose of skepticism is the best response to Tesla’s latest grand plan.

I would love to hear others thoughts on these statistics and projections, so please hit us up on LinkedIn or our X.com account and let us know what you think. Where do you see the future of AI taking us?

Must-Read Articles

Mike's Musings

AI Tip
The Future of Coding Education in an AI-Driven World

As someone deeply involved in the tech industry, I recently had a great conversation about the future of coding education in our AI-driven world. Rico asked me about my vision for teaching coding, from initial concept to functional application, and it got me thinking about the rapid changes we’re seeing.

From my perspective, several key areas are becoming increasingly important:

Communication is crucial. I shared an anecdote about architecting an app by talking to ChatGPT while driving to work. The ability to interact naturally with AI tools, even through voice, is a game-changer.

Networking is more vital than ever. In a world where AI can generate thousands of resumes, personal connections make a huge difference. I emphasized the importance of making friends in the industry - showing up to local meetups and engaging with people face-to-face.

Understanding fundamentals of application design is essential. This isn’t just about writing code; it’s about being able to recognize when AI tools are giving you incorrect or irrelevant information.

Testing and benchmarking skills are critical. We can now quickly generate code to test AI-built applications, making it easier than ever to verify and optimize AI-generated solutions.

The big picture matters. Being able to conceptualize and design applications at a high level is becoming more important than writing every line of code yourself.

One tip I shared was to break tasks into smaller, atomic units when working with AI tools. It’s often more effective to generate code piece by piece rather than trying to create entire applications in one go.

I also noted that newer programming languages and frameworks might still pose challenges for AI tools, as they simply don’t have as much training data to work with compared to more established technologies.

As we wrapped up our chat, I reflected on how traditional coding courses might adapt to these changes. It’s clear that the focus of coding education is shifting, and it’ll be fascinating to see how institutions respond to this new reality. The combination of strong communication skills, networking abilities, and a solid understanding of application architecture and testing will be key for future developers.

Mike’s Favorites
Clip: Elon Musk’s Beer-Pouring Optimus Robots Are Not Autonomous

An attendee of Elon’s afterparty, Robert Scoble (one of the creators of Siri) asked one of the Optimus robots bartending whether or not it was AI. The robot’s response was: “Today, I'm assisted by a human”. I think it’s important to understand that while the Optimus robots are indeed an innovative tech, even Elon isn’t allowing them full autonomy at his own event.

@itsnickholiday

What really happened at Elon Musk Optimus and cyber taxi event #Optimus #CyberTaxi #ElonMusk #Robot #event

Video: Run ALL Your AI Locally in Minutes (LLMs, RAG, and more)

Great video on how to host AI workflows on your own hardware. With privacy concerns, costs, and an abundance is good open-source models like llama 3.1… hosting your own AI services hardware is becoming more and more viable. This video from @ColeMedin walks you through the process.

Thanks for checking out my section! If you have an idea for the newsletter or podcast, feedback or anything else, hit us up at [email protected].

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Quote of the week: "The future belongs to those who embrace change, not fear it.”