Beginners in AI

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Welcome to this week's edition of Beginners in AI, where we explore the latest trends, tools, and news in the world of AI and the tech that surrounds it. Like all editions, this is human curated and published with the intention of making AI news and technology more accessible to everyone. 

This week, we break down what GPT-4.5 really is (and what it isn’t). Meanwhile, Amazon is diving deeper into quantum computing with Ocelot, and Alexa might be getting a major AI makeover. Plus, new AI text diffusion models could revolutionize how machines generate language, while DJI pushes the limits of drone autonomy. And in robotics, self-building humanoid robots are taking their first steps toward a sci-fi reality.

AI TOP STORY

ChatGPT 4.5: Mixed Reviews and Lower Expectations

What’s Happening
The AI community had been buzzing with speculation about OpenAI’s next big release, but GPT-4.5 is not what many expected. Unlike previous leaps in AI, this update isn’t classified as a "frontier model," meaning it doesn’t introduce groundbreaking capabilities beyond what current AI can do. Instead, it’s a refinement of GPT-4, improving efficiency, speed, and usability rather than redefining AI’s boundaries.

Why It Matters
Many assumed OpenAI’s next model would be a stepping stone toward artificial general intelligence (AGI), but this clarification resets expectations. GPT-4.5 is likely a transitionary update before GPT-5, focusing on making AI more cost-effective and scalable rather than introducing disruptive new intelligence. This move signals that OpenAI is taking a more incremental approach. There's nothing inherently wrong with this approach. However, it does clash with statements from OpenAI CEO Sam Altman, who posted X(formerly Twitter) prior to the release “It is the first model that feels like talking to a thoughtful person to me.”

How It Affects You
Don’t expect a revolution from this release—GPT-4.5 won’t be rewriting the AI rulebook just yet. This signals a shift toward more practical AI applications rather than the constant race for radical breakthroughs. Recent trends include Microsoft canceling datacenter plans and Grok 3, despite its massive training hardware, advanced abilities, and powerful reasoning, not yet living up to the breakthrough claims that people were expecting of it on initial release. This does not signal an AI winter immediately, but it does look like a bit of a slowdown from the rapid pace we've been accustomed to.

LAST WEEK IN AI AND TECH

DJI’s Drone-in-a-Box Revolution
DJI has unveiled Dock 3, a next-gen drone station designed for fully autonomous drone operations. This technology allows drones to take off, land, and recharge independently, opening doors for applications in security, agriculture, and disaster response. It also comes with AI-assisted navigation and precision landing. Drone development is one of the most important categories to keep an eye on. The technology is getting cheaper, more advanced, and more prolific across the world every day. Drone warfare is quickly reshaping the future of battle.

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Quantum Leap: Amazon's Ocelot Chip
Amazon is making big moves in quantum computing with Ocelot, its first quantum chip. This development places Amazon in direct competition with Google, IBM, and as of last week, Microsoft(see Grok 3 Breaks the AI Mold: Elon Musk’s New Model Never Stops Learning) in the race to build practical quantum computers. While details on performance remain vague, the move suggests Amazon Web Services (AWS) is serious about integrating quantum computing into its cloud offerings. This could mean breakthroughs in cryptography, logistics, and AI acceleration in the near future. Following Amazon's current business model, it may even be feasible for non-scientists to even rent use of quantum computers.

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Alexa Gets Smarter, (and Prettier?)
Amazon is betting big on Alexa, with Panos Panay leading efforts to evolve it beyond a voice assistant into a true AI-powered helper. The company hints at major upgrades, including better natural language processing, real-world contextual understanding, and AI-generated responses that feel more natural. It should be capable of complex scheduling and booking reservations, Interpreting and explaining complex documents, and even integration with the Ring camera system. According to Amazon CEO Andy Jassy, “there’s some really beautiful hardware we have coming out this fall” to go with the major software upgrade.

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AI Text Diffusion: Meaning From Noise
New AI model from company Inception Labs that recently came out of stealth is rewriting the rules of text generation. Instead of predicting the next word like traditional transformers models(ChatGPT for example) going from left to right, these diffusion-based models "pull words from noise," leading to significantly faster and more coherent text generation and showing everything all at once. This breakthrough could mean near-instant AI-generated content with fewer hallucinations—perfect for chatbots, writing tools, and even AI-generated scripts. Test the model’s speed for yourself here, toggling the diffusion effect button at the top of the page.

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GibberLink: AI-Powered Gibberish with a Purpose
A new AI experiment, GibberLink, takes nonsense text generation to new heights, using AI to create patterns in seemingly meaningless gibberish. While it may sound bizarre, the project explores how structured randomness can aid in cryptography, CAPTCHA tests, and even creative writing prompts. This is in stark contrast to the recent addition of reasoning models in AI showing the chain of thought that produced the output.

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TECH TERMS TO KNOW

AI Winter refers to periods when interest and funding in artificial intelligence research significantly decline, typically due to unmet expectations or technological limitations. These downturns follow cycles of hype and inflated promises that the technology of the time couldn’t fulfill. They're not unlike crypto winters in this regard.

Timeline of AI Winters

First AI Winter (1974–1980)

• Triggered by the Lighthill Report (1973), which criticized early AI advancements as impractical.

• Governments slashed funding after overpromised breakthroughs in speech recognition and problem-solving failed to materialize.

Second AI Winter (1987–1993)

• Caused by the collapse of the LISP machine market (specialized computers for AI programming).

• Expert systems (early AI designed for specific tasks) became too expensive and inflexible, leading to disillusionment.

While there were smaller slowdowns, these two periods are the most widely recognized AI winters. The field has since rebounded with advancements like machine learning and neural networks, which addressed earlier limitations.

TOOL SPOTLIGHT (non-sponsored)

Mark is a physical bookmark integrated with artificial intelligence. It combines traditional bookmarking with advanced technology to help readers track their progress, engage more deeply with their reading material, and access additional insights or summaries related to the content they are reading.

What It Does

• Tracks Reading Progress: Mark keeps a record of where you left off in a book, ensuring you never lose your place.

• Provides Contextual Insights: Using AI, it can offer summaries, definitions, or explanations of complex terms or concepts in the text.

• Syncs with Digital Devices: Mark may connect to apps or devices to store your reading history and provide recommendations for further reading.

• Facilitates Note-Taking: Some versions of AI-powered bookmarks allow users to highlight sections or take notes digitally while reading.

What It’s Good For

• Enhanced Learning: Ideal for students or professionals who need additional context or quick references while reading.

• Convenience: Helps readers seamlessly switch between physical and digital formats without losing track of their progress.

• Improved Retention: By offering summaries and insights, Mark aids in better understanding and retention of information.

• Personalized Reading Experience: AI integration allows for tailored recommendations based on reading habits and preferences.

ROBOTICS AND AI

Apptronik’s latest humanoid robots are taking automation to the next stage—by working on building future generations of robots themselves. Using a combination of AI vision, dexterous robotic arms, and machine learning, these humanoids can assemble key components, reducing reliance on human labor in robotic production. While still in early stages, this milestone hints at a future where AI-driven robots play a role in their own evolution, accelerating progress in automation.

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TRY THIS PROMPT (copy and paste into AI ChatGPT, Grok, Claude, Gemini)

Simple Problem Solver(this can be used with advanced voice modes too for ChatGPT, Perplexity, and Grok 3)

I'm struggling with [problem]. Role-play a conversation with me where you ask clarifying questions and help me identify the root cause of the problem.

DID YOU KNOW?

The Internet Weighs as Much as a Strawberry – If you could weigh all the electrons in motion that make up the internet, it would be about 50 grams—roughly the weight of a single strawberry. This estimate comes from physicist Russell Seitz, who calculated the weight of the electrons in motion that are required to store and transmit all the data on the internet.

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AI-GENERATED IMAGE OF THE WEEK

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Thank you for reading. We’re all beginners in something. With that in mind, your questions and feedback are always welcome and I read every single email!

-James

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