Gemini 2.5 Flash creates an actually mildly amusing New Yorker cartoon. (As far as I can tell, this is the first time that this joke has been used)
@emollick
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Google’s New Image Generator Demonstrates Advanced Generative AI Capabilities
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An example of the new Google image generator. I gave it a random picture I took:
"make this a napoleon crochet book instead" (note it made changes in consistent style)
"there should be a tiny sheep hidden among the blue yarn on the shelf to the right"
"you misspelled Napoleon" -
AI Impact on Entry-Level Jobs and Workforce Automation
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There has not been a lot of evidence so far that AI is actually impacting jobs. This paper suggests this may be starting, showing a decrease in entry-level job openings relative to experienced ones & in the jobs where AI is mostly automates, not augments, work (like coding).
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Microsoft Sustainability Head Discusses AI Environmental Impact
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Some comparisons from a Nature commentary by the head of sustainability at Microsoft: https://
media.nature.com/original/magaz
ine-assets/d41586-025-02641-4/51368154
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AI Model Struggles With Analog Clock Reading Task
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It did horse riding on astronaut first try, but didn't pull off an analog clock reading 3pm, which remains the great undefeated test (it is possible that better prompting could help)
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Accessing Nano Banana Image Editing Model in LM Arena
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(The only way to use it now is to go to LM Arena, click the image icon, and get lucky as you will be randomly given a model, if you upload an image to the arena to work on, you are more likely to get nano banana because there are fewer image editing models than image making ones)
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Nano Banana: Major Breakthrough in AI Image Generation Technology
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Nano banana is a genuinely impressive jump forward in AI image generation, a field I have followed closely. Whenever it is officially released, by whichever firm created it, I think it will have a significant impact on the applicability of AI image generation for real-world tasks
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Measuring AI Model Improvements Through Expert-Evaluated Tasks
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I only say partially since we can measure the impact of AI improvement more directly on meaningful tasks: better coding, fewer hallucinations in summarizing a complex medical case, etc. In these situations, experts can see meaningful small differences among models as they improve
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Google Gemini vs Mistral: Environmental Impact Analysis
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The Verge publishes a piece criticizing some of these measures: https://
theverge.com/report/763080/
google-ai-gemini-water-energy-emissions-study
… And Mistral's audited report for their older model gave larger amounts of water (50 mL) and carbon emissions (1.14g) per average query. https://
mistral.ai/news/our-contr
ibution-to-a-global-environmental-standard-for-ai
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