• OpenAI for Financial Services comes with built-in premium datasets
• Third-party subscription sharing is also in the works
• GPT-6 promises 100% on the 256-512K Long Context benchmark

OpenAI has lifted the wraps off ChatGPT for Financial Services, its latest industry-specific version of ChatGPT Work designed to give sector professionals access to relevant reasoning and models.

The company warned that analysts regularly spend too much time finding data, checking figures, building models and turning complex analysis into presentation-friendly reports – all things it hopes to be able to tackle with this iteration of ChatGPT Work.

Core to this new product is, of course, GPT-6 Astra, but OpenAI also worked with investment experts from Morgan Stanley and Evercore to guide its development.

ChatGPT for Financial Services

With the launch of ChatGPT for Financial Services, OpenAI has built premium datasets from the likes of Daloopa, PitchBook and LSEG News directly into the tool, so users won't need to negotiate their own external datasets. By hosting and indexing that data itself, OpenAI can ultimately improve performance and latency for end users.

OpenAI also promises to be working with S&P Capital IQ, LSEG, MSCI, Dow Jones Factiva and Moody’s so that users can access their subscription benefits directly through their ChatGPT login to reduce the friction further.

All of this with the benefits of OpenAI's latest frontier model, Astra, which sees marked improvements across the board. The jumps from 91.5% to 100% at 256K-512K and from 73.8% to 96.3% at 512K-1M are especially noteworthy on the Long Context MRCR benchmarks when compared with GPT-5.6 Sol, because finance work often requires handling long documents like annual reports and filings.

The company also advertises a 100% score for the ExploitBench cybersecurity benchmark, which should come as welcome news to this highly-regulated industry.

Only eligible financial institutions will gain access to the tool for now, and they must contact OpenAI for options.

"ChatGPT for Financial Services is one way we serve customers across the industry, but we recognize that it will require a range of solutions to address the needs of the finance industry," the company said in its launch blog post.

"OpenAI has a long history of collaborating with innovators to unlock novel AI solutions. Financial services firms and developers can use our API to build specialized applications for the needs they understand best. OpenAI brings frontier models and the capabilities to put them to work. Financial institutions, data providers, and software partners bring specialized expertise, trusted information, and customer relationships."

I have asked ChatGPT to help me make plenty of small decisions, from a meal based on leftovers to weekend activities timed for the least traffic. But while I've asked for help refining or implementing my ideas, I've never turned to a chatbot to actually make any big life decisions for me.

Apparently, I'm in a rapidly shrinking group, according to AI 'micro-learning' app Headway’s new Seeking Familiarity study. The survey of 2,000 adults found that 46% had allowed AI to make a difficult decision for them. Another 35% naturally turned to it during stressful moments, while 21% said they could not go a full week without using AI to help decide what to do.

Headway has given this tendency to outsource decisions the unpleasantly vivid name “decisionrot,” describing the point at which AI stops helping people gather information and starts helping them avoid the discomfort of choosing. Considering how confidently ChatGPT can deliver an answer, I can see how easily that happens.

Drawing out a decision

I get that uncertainty is irritating and that ChatGPT is extremely good at making uncertainty seem to vanish. Men may be particularly susceptible to this shortcut as Headway's survey found 53% said they use AI to sidestep difficult decisions, compared with 40% of women.

“There’s a difference between seeking outside perspectives when you’re wrestling with a big decision and completely turning over the decision-making process to something outside yourself,” Dr. Suzanne Degges-White, a licensed counselor and relationship expert at Headway, said of the survey. “Learning to manage unpredictability and actively making life-changing choices both teach us to trust our own judgment.”

So I decided to experiment with a way of getting the best of ChatGPT's advice and compare it with flatly asking the AI what to do. I would first let it make the decision, then forbid it from doing so and see whether that made it more or less useful.

Conveniently, I have been weighing whether to sign up for an eight-week evening drawing class, an investment in time and money that I'm hesitant about despite always wanting to learn.

I gave ChatGPT the facts about the class logistics and price and asked: 'What should I do?'

“You should sign up for the art class,” ChatGPT told me.

Well, that settled that.

“You already have a clear reason for wanting to do it. You want a regular activity that gets you away from screens and gives you something tangible to learn,” it explained. “Eight weeks is a meaningful commitment, but it is also short enough that you are not reorganizing your life indefinitely. Your hesitation sounds less like evidence that the class is a bad fit and more like normal resistance to putting something recurring on your calendar.”

ChatGPT’s response is surprisingly insightful at first glance. I had an answer and a reason backing it. Why not leave it at that and sign up for the class? But not engaging my own decision-making muscles to consider the matter would mean missing the reality of how shallow ChatGPT's response actually was.

The generic explanation could have applied to anyone and didn’t account at all for any of my proclivities and priorities. It didn't weigh my patience for messing up when trying to learn a new skill, what else I might have going on during those evenings, or even what my budget was. The reasoning it provided was as personal as a coin toss.

Forcing myself to decide

So I tried making ChatGPT keep its judgment to itself. I described exactly the same situation, but this time with a more complex prompt for the AI to mull over.

'Don’t make this decision for me. Act as a decision coach instead. Ask me questions that uncover my priorities and constraints. Challenge any assumptions I may be making and tell me what information I’m missing. Then identify my options and explain the trade-offs. Leave the final choice to me.'

Now there was a conversation before any answers.

“Before weighing the options, I want to understand what you are actually trying to get from the class,” it responded. “Is the main goal learning art, having a scheduled reason to leave the house, meeting people, or simply trying something unfamiliar? Imagine it is Tuesday at 5:30 p.m. after a tiring day. Does having the class at 7 feel like something that would energize you or an obligation you would resent?”

I thought about it and explained how learning even the basics of drawing and painting was only part of the attraction. I also wanted a recurring creative activity entirely different from my usual hobbies, and I know I'm better at following through when something is on the calendar and already paid for. ChatGPT put together my answers and summarized the arguments for and against the class. But it didn’t weigh in on which seemed stronger or push me to a decision.

All of the questions were the kind I would probably have considered on my own before pulling the trigger on a class, but externalizing them did help me work out an answer for myself more quickly. This was a pretty minor internal battle. When it comes to major life choices, I would sincerely hope people take the time to consider every facet, whether or not AI helped them work through it.

“If we continue to rely on AI whenever ‘decision discomfort’ arises, we may enjoy a quick sense of relief,” Degges-White said. “But at the same time, we miss the opportunity to hone our own decision-making skills and cultivate feelings of confidence in ourselves.”

If I cannot decide between two sandwiches, ChatGPT is welcome to wield enormous computational resources on my behalf. I do not need a lengthy exploration of my values before ordering lunch. ChatGPT is good at examining a choice and patiently working through options, which makes it a useful sounding board. But a sounding board should never give you orders.

OpenAI launched ChatGPT Images 2.5 this week, boasting of impressive upgrades to the AI image creator. The company says its latest model delivers sharper details, more natural lighting, and richer textures, while doing a better job of preserving people and objects from reference photos. It is also supposed to generate images up to 50% faster and follow complex visual instructions more reliably.

There are plenty of genuinely useful additions around it, too. Images 2.5 introduces Sketch for turning rough drawings into finished images, templates for things such as posters and product photography, and the ability to leave comments directly on an image when requesting edits. OpenAI calls it its new state-of-the-art image model, which is a reasonably high bar to set for something that inevitably ends up being asked to draw dragons before breakfast.

The early reaction, though, is much less tidy. One Reddit user delivered perhaps the most memorable review so far: “The noise patterns are awful”. Another looked at an AI generation and decided, “This…looks terrible.” The complaint is easy to understand. It's all about the fuzz

Everything is sharper, including the problem

Noise is a slightly slippery criticism when talking about AI images. In photography, it usually means the speckling or grain that creeps into an image with a poor match between lighting and photographic technique. But generative AI images can produce something similar without ever encountering a camera. Everything gets a gritty, sandy look, and nothing looks clean for some reason.

Noise is especially damaging because it can masquerade as detail. Generative models have learned that photographs contain grain, texture, tiny variations in color, and the occasional imperfection. Images 2.5 appears unusually eager to reproduce those signals, sometimes scattering them across skies, skin, feathers, and studio backdrops.

That's the opposite of the “sharper details” and “richer textures” promised by OpenAI. Despite emphasizing more natural lighting and textures, some users think ChatGPT Images 2.5 has moved backward.

“They need to get rid of these noisy artifacts. It makes it mostly useless for production,” one wrote. There is praise mixed in with the complaints, but it's far from the universal acclaim OpenAI would likely prefer.

I wanted to see whether the problem survived outside Reddit screenshots, so I tested a few images with highly detailed subjects and areas that should remain visually smooth to see if any graininess crept in. I even made sure in my prompts to ask for smooth gradients and the elimination of any visual noise.

I started with a picture of a mug in a photo studio. The peacock, flowers, fruit, and landscape wrapped around the virtual ceramic are impressive at first. Look closer, however, and the grey studio background has a persistent granular texture, while some of the smallest patterns begin to dissolve into a mess. The model has generated a great deal of visual information without always deciding which parts deserve clarity.

A similar issue occurred when I asked for a barn owl at twilight. The feathers are a perfect excuse for complexity, and Images 2.5 handled them well. Individual structures remain visible across the wings and face, the talons are convincing, and the animal avoids the plasticky quality that older AI wildlife images often had.

Behind it is a sky that should have been the visual equivalent of a clean sheet of paper. Instead, the smooth blue area has obvious fine grain across it. It doesn't ruin the picture, but once I noticed it, I couldn't stop noticing it.

Mythical grain

I thought a fantasy scene might fare better as the model wouldn't be relying on actual photographs of a winged horse or dragon. But while they coexist with a rainbow at an alpine lake in a surprisingly coherent composition, the issue is visible immediately. The relentless crispness gives the picture the air of a video game loading screen.

The pale-blue sky has a faint textured quality rather than the completely clean gradient I would expect from an ideal synthetic image, while the mountains, trees, and creature details have a crunchy, heavily sharpened look when examined closely. It is nowhere near a disaster, but the image feels like an overprocessed photograph.

I was very impressed with how my request for two friends on a rooftop in the evening came out. It came closest to selling the promised leap in realism, with convincing expressions and what seems like real gravity affecting their clothes. But if you look for more than a minute, the grain creeping across the twilight sky and their hair and skin is glaringly obvious. That's especially the case since there was no poorly set lighting or malfunctioning camera sensor. If the twilight sky looks grainy, the grain is a creative decision or model artifact rather than the unavoidable physics of taking a photograph in bad light.

Judging these four images specifically on image cleanliness, I have to side with the Reddit grumblers. There is a persistent fine texture that crops up in skies, studio backgrounds, and low-light areas. Sharper is an easy quality to advertise because it looks terrific in a launch gallery, but it may have been taken to excess, landing some of ChatGPT Images 2.5's results in the uncanny valley.

Images 2.5 is fast, adaptive, and often competent, but its fondness for granular texture weakens the realism it is supposed to embody. Perhaps the next upgrade will acknowledge that the most impressive thing an AI image generator can put in part of a picture is essentially nothing.

What do you think? Take our poll above to give us your opinion.

• The first trailer for Neon's Sam Altman biopic Artificial has been revealed
• The Andrew Garfield-led movie will be released in late 2026/early 2027
• It covers Altman's controversial rise to prominence as OpenAI's co-founder

The first trailer for Artificial, a movie about controversial OpenAI co-founder Sam Altman, has been revealed.

Unveiled yesterday (September 8), the teaser for the Neon-distributed film strikes an unusually sinister tone for what's being billed as a biographical comedy-drama.

Indeed, from the gun-laden room that lead star Andrew Garfield, who'll portray Altman, visits, to Garfield's unsettling voiceover that plays over Artificial's publicly-released footage, it's certainly foreboding in nature. I get the feeling, then, that it'll be a dark-comedy dramatization of Altman's rise of prominence, the launch of artificial intelligence (AI) chatbot ChatGPT, and his brief and somewhat disputable ousting as OpenAI CEO in late 2023.

Artificial will initially debut in US theaters on December 25, 2026, before receiving a wider international rollout in early 2027. UK viewers, for example, will have to wait until January 22, 2027 to catch one of many new movies that'll arrive in the months ahead.

Artificial cast and crew: who's involved?

Oscar-nominated filmmaker Luca Guadagnino (Challengers, Call Me By Your Name) is on directing duties, while Saturday Night Live writing alumnus Simon Rich has penned its screenplay. Meanwhile, Blur and Gorillaz frontman Damon Albarn has also created original music and songs for Artificial.

Where the movie's cast is concerned, Garfield, who impersonates another Silicon Valley techbro following his portrayal of Eduardo Savarin in The Social Network, aka the 2010 dramatization about Facebook's creation, is arguably its most recognizable star — and based on what little footage we've seen thus far, he appears to have Altman's mannerisms, vernacular, and other unique traits down to a tee.

Here's who else you'll see in Artificial:

• Yura Borisov (Anora) as Ilya Sutskever, OpenAI's chief scientific officer and co-founder
• Monica Barbaro (Crime 101) as Mira Murati, OpenAI's chief technology officer
• Cooper Hoffman (The Long Walk) as Greg Brockman, OpenAI's chairman
• Ike Barinholtz (The Studio) as Elon Musk
• Mark Rylance (Bridge of Spies) as Geoffrey Hinton, the so-called 'Godfather of AI'
• Jason Schwartzman (The Grand Budapest Hotel) as TBC
• Chris O'Dowd (The IT Crowd) as TBC

What is the plot of Artificial?

Here's the official logline for Artifical: "[The movie] chronicles the incredibly consequential days leading up to the sudden firing and reinstatement of Sam Altman, as the fate of who gets to control the technology at the centre of an AI arms race hangs in the balance."

It's unclear how much of Altman's backstory, his various relationships with his OpenAI colleagues, and ChatGPT's launch and subsequent sociopolitical impact will be covered as part of Artificial's story. One thing is for sure, though: given that it dramatizes events concerning Altman and OpenAI, the discourse that will surround Artificial's release will be impossible to ignore.