AI Highlights

My top-3 picks of AI news this week.

OpenAI
1. GPT-4o Image Mania

OpenAI has blown up social media this week with their latest GPT-4o image generator that has everyone talking. They’ve integrated advanced image-generation capabilities directly into ChatGPT, and the results are genuinely impressive.

• Multimodal integration: Image generation is now a core capability of the language model itself, allowing for seamless conversation-based image creation and refinement.

• Text rendering: GPT-4o excels at accurately rendering text within images, making it ideal for creating diagrams, signs, and other visual communication tools.

• Contextual understanding: The model can analyse uploaded images and maintain consistency across multiple iterations, a serious leap in visual creation.

Alex’s take: I think this is the tipping point where image generation within AI models becomes truly mainstream. Midjourney stole the thunder for the last few years. Then, new entrants like Ideogram and Flux created some waves, but the consistency of GPT-4o’s image gen capabilities (both in style and composition with text) is leaps ahead of the rest. One of my favourite use cases of this feature is that people are now extracting image data and using this for style replication.

Google DeepMind
2. Google Unlocks Gemini 2.5

Google DeepMind has unveiled Gemini 2.5, its most intelligent AI model yet, designed specifically as a “thinking model” to tackle increasingly complex problems.

• Leading performance: Gemini 2.5 Pro Experimental tops the LMArena leaderboard by a significant margin and excels across benchmarks requiring advanced reasoning.

• Enhanced reasoning capabilities: The model scores 18.8% on Humanity's Last Exam without tool use, setting a new state-of-the-art benchmark for complex knowledge and reasoning.

• Impressive coding skills: Achieves 63.8% on SWE-Bench Verified with custom agent setup, with the ability to create visual web apps and executable game code from simple prompts.

Alex’s take: This is a serious leap forward in AI reasoning capabilities. If it’s better at coding than Claude 3.7 Sonnet (200K context) while having a 1 million token context window (2 million coming soon), it will become very useful as a coding agent. This is now turning into a four-horse race with Gemini, Grok, Claude and ChatGPT all competing for the top spot.

xAI
3. Musk Merges His AI and Social Media Empires

Elon Musk has announced that his artificial intelligence company xAI has acquired his social media platform X (formerly Twitter) in an all-stock transaction.

• Valuation: The deal values xAI at $80 billion and X at $33 billion ($45B less $12B debt), despite Musk originally purchasing Twitter for $44 billion in 2022.

• Integration: The merger combines data, models, compute, distribution and talent between the two companies, which were already sharing significant resources.

• AI integration: xAI has been using data from X to train its models, with its chatbot Grok already being a prominent feature on the platform.

Alex’s take: I suspect this merger will accelerate the integration of Grok across X while giving xAI access to one of the world’s largest real-time data sources. This is a big step in creating an “everything” app, much like WeChat in China. I suspect payments will be coming soon, and it will become almost like a digital twin to its users.

Content I Enjoyed

The Convergence of Humans and Machines

This week, I stumbled across a BBC Archive interview from 1965 with renowned science fiction author Isaac Asimov.

In the interview, he shared a prolific idea surrounding the convergence of humans and robots into hybrid entities.

On the one hand, he foresaw robots becoming more human-like, while humans would increasingly incorporate artificial components. Asimov thought that at some time in the future, it might become increasingly challenging to distinguish between the two, raising important questions around what “being alive” and “consciousness” truly mean.

We only have to look back over the last 5 years to see some early glimmers of this in action.

We already have humanoid robots starting to walk and run like us. Take, for example, Boston Dynamics’ recent demo of Atlas.

What about neural networks mimicking our brains, and the transformer architecture of LLMs like ChatGPT being essentially a compression of the internet, predicting the next word in a sequence of words using human language?

And whilst artificial systems are becoming more “human”, we humans are already experimenting with brain-computer interfaces like Neuralink alongside advanced prosthetics and artificial organs replacing failing human ones.

Will we see a hybrid species in the future? I believe so. Yet, it will require humanity to deeply understand the ethical and societal implications such integration would bring and what its lasting impact might be.

Idea I Learned

The Ghibli Creator is Disgusted by AI

OpenAI’s advanced image generator was introduced into GPT-4o on Tuesday, and it has been a total frenzy ever since.

My feeds on LinkedIn and X this week have been flooded with Ghibli Studio-style images.

However, Hayao Miyazaki, co-founder of Studio Ghibli himself, isn’t quite as enthralled.

I discovered this 2016 video of Miyazaki from YouTube that captures his perspective:

“AI-generated animation is an insult to life itself.”

Each film from his studio is hand drawn and painted with watercolours. Each frame (typically 60,000 to 70,000 per film) means this process can take years. Now, anyone can create a Ghibli-style image using GPT-4o.

This highlights the key concerns the world needs to address in how these AI tools are trained to imitate styles.

Is OpenAI violating copyright law?

I enjoyed sinking my teeth into this article, which highlights the perspective of an intellectual property lawyer on the whole situation.

The “TL;DR” is that OpenAI does not appear to be breaking the law as an image’s style is not explicitly protected by copyright. However, the training on copyrighted works is still up in the air as to whether it falls under fair use protections.

It made me think of what Adobe is doing with its Firefly model. When I attended Adobe MAX in 2024, Adobe unveiled Firefly Video, touting it as “the first commercially safe video generation model.”

This claim stems from Adobe’s strategy to train Firefly on a dataset with known provenance—using Adobe Stock images, openly licensed content, and public domain materials where copyright has expired.

This approach contrasts with the uncertainty surrounding OpenAI’s training data, where critics, including intellectual property lawyers, question whether scraping copyrighted works from the web for AI training falls under fair use.

If a model like OpenAI’s isn’t as “commercially safe” due to potential legal risks, some users might actually prefer models like Firefly for their transparency and reduced risk of copyright infringement lawsuits.

But right now, there’s a lot of tension in the industry as courts continue to grapple with whether training AI on copyrighted material qualifies as fair use or constitutes infringement. According to the U.S. Copyright Office and legal experts, for a work to be copyrighted, it must have a human author, but the legal status of AI-generated content remains murky.

Until clarity is found, I believe the debate over whether tools like GPT-4o or Firefly are truly “safe” will continue to spark discussions across social media, legal forums, and creative communities, especially as artists like Miyazaki voice their concerns about the erosion of traditional craftsmanship in the face of AI.

Quote to Share

Texas private school’s use of new “AI tutor” rockets student test scores to top 2% in the country:

“We use an AI tutor and adaptive apps to provide a completely personalized learning experience for all of our students, and as a result our students are learning faster, they're learning way better. In fact, our classes are in the top 2% in the country.”

At Austin’s Alpha School, students spend just two hours daily with AI tutors, using the remainder of their day to develop skills like public speaking and financial literacy.

This approach effectively solves what educators call “Bloom's 2 Sigma Problem”—the finding that one-on-one tutoring dramatically improves learning outcomes but has historically been too expensive to implement widely.

I think the key advantage is how AI allows students to ask unlimited questions without fear of judgment.

It’s very common for people to hold back from asking questions for fear of looking “dumb” in the eyes of fellow students and the teacher for not getting it.

I struggled with this anxiety a lot while going through school. Not understanding something, asking an initial question, still not getting it, and then being too intimidated to keep asking for clarification.

As Alpha School expands across the US, we’re witnessing education’s potential future where technology handles personalised instruction. At the same time, human teachers focus on providing what machines cannot: emotional support and real-world guidance.

Source: Fox News

Question to Ponder

I saw a great answer to this recently. Rhona D’Arcy uses AI to monitor her 86-year-old mum Heather, who has vascular dementia but refuses to leave her home and lives three hours away from her daughter.

The AI system learns Heather's normal patterns—room movements, bathroom usage, fridge opening—and alerts Rhona when something’s off.

Economists say similar systems could save the NHS £1.2bn by 2035, but I think the true value transcends money.

Critics worry face-to-face care might be cut. As Dr. Collingham notes, “The cornerstone of good care is human connection.” But for Rhona, “It doesn't replace the care, it augments it.”

Another great example is the Ray-Ban Meta Glasses and their partnership with “Be My Eyes” to help people who are blind or have low vision. One use case in particular that caught my eye (if you’ll pardon the pun) is of the glasses helping a blind veteran navigate their daily life.

This is a future we can all get excited about.

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