logo
I tested Gemini's latest image generator and here are the results

I tested Gemini's latest image generator and here are the results

Back in November, I tested the image generation capabilities within Google's Gemini, which was powered by the Imagen 3 model. While I liked it, I ran into its limitations pretty quickly. Google recently rolled out its successor — Imagen 4 — and I've been putting it through its paces over the last couple of weeks.
I think the new version is definitely an improvement, as some of the issues I had with Imagen 3 are now thankfully gone. But some frustrations still remain, meaning the new version isn't quite as good as I'd like.
How often do you create images with AI?
0 votes
It's a daily thing for me.
NaN %
Maybe once per week.
NaN %
A few times per month.
NaN %
Never.
NaN %
So, what has improved?
The quality of the images produced has generally improved, though the improvement isn't massive. Imagen 3 was already generally good at creating images of people, animals, and scenery, but the new version consistently produces sharper, more detailed images.
When it comes to generating images of people — which is only possible with Gemini Advanced — I had persistent issues with Imagen 3 where it would create cartoonish-looking photos, even when I wasn't asking for that specific style. Prompting it to change the image to something more realistic was often a losing battle. I haven't experienced any of that with Imagen 4. All the images of people it generates look very professional — perhaps a bit too much, which is something we'll touch on later.
One of my biggest frustrations with the older model was the limited control over aspect ratios. I often felt stuck with 1:1 square images, which severely limited their use case. I couldn't use them for online publications, and printing them for a standard photo frame was out of the question.
While Imagen 4 still defaults to a 1:1 ratio, I can now simply prompt it to use a different one, like 16:9, 9:16, or 4:3. This is the feature I've been waiting for, as it makes the images created far more versatile and usable.
Imagen 4 also works a lot more smoothly. While I haven't found it to be noticeably faster — although a faster model is reportedly in the works — there are far fewer errors. With the previous version, Gemini would sometimes show an error message, saying it couldn't produce an image for an unknown reason. I have received none of those with Imagen 4. It just works.
Still looks a bit too retouched
While Imagen 4 produces better images, is more reliable, and allows for different aspect ratios, some of the issues I encountered when testing its predecessor are still present.
My main problem is that the images often aren't as realistic as I'd like, especially when creating close-ups of people and animals. Images tend to come out quite saturated, and many feature a prominent bokeh effect that professionally blurs the background. They all look like they were taken by a photographer with 15 years of experience instead of by me, just pointing a camera at my cat and pressing the shutter.
Sure, they look nice, but a 'casual mode' would be a fantastic addition — something more realistic, where the lighting isn't perfect and the subject isn't posing like a model. I prompted Gemini to make an image more realistic by removing the bokeh effect and generally making it less perfect. The AI did try, but after prompting it three or four times on the same image, it seemed to reach its limit and said it couldn't do any better. Each new image it produced was a bit more casual, but it was still quite polished, clearly hinting that it was AI-generated.
You can see that in the images above, going from left to right. The first one includes a strong bokeh effect, and the man has very clear skin, while the other two progress to the man looking older and older, as well as more tired. He even started balding a bit in the last image. It's not what I really meant when prompting Gemini to make the image more realistic, although it does come out more casual.
Imagen 4 does a much better job with random images like landscapes and city skylines. These images, taken from afar, don't include as many close-up details, so they look more genuine. Still, it can be a hit or miss. An image of the Sydney Opera House looks great, although the saturation is bumped up quite a bit — the grass is extra green, and the water is a picture-perfect blue. But when I asked for a picture of the Grand Canyon, it came out looking completely artificial and wouldn't fool anyone into thinking it was a real photo. It did perform better after a few retries, though.
Editing is better, but not quite there
One of my gripes with the previous version was its clumsy editing. When asked to change something minor — like the color of a hat — the AI would do it, but it would also generate a brand new, completely different image. The ideal scenario would be to create an image and then be allowed to edit every detail precisely, such as changing a piece of clothing, adding a specific item, or altering the weather conditions while leaving everything else exactly as is.
Imagen 4 is better in this regard, but not by much. When I prompted it to change the color of a jacket to blue, it created a new image. However, by specifically asking it to keep all other details the same, it managed to maintain a lot of the scenery and subject from the original. That's what happened in the examples above. The woman in the third image was the same, and she appeared to be in a similar room, but her pose and the camera angle were different, making it more of a re-shoot than an edit.
Here's another example of a cat eating a popsicle. I prompted Gemini to change the color of the popsicle, and it did, and it kept a lot of the details. The cat's the same, and so is most of the background. But the cat's ears are now sticking out, and the hat is a bit different. Still, a good try.
Despite its shortcomings, Imagen 4 is a great tool
Even with its issues and a long wishlist of missing functionality, Imagen 4 is still among the best AI image generators available. Most of the problems I've mentioned are also present in other AI image-generation software, so it's not as if Gemini is behind the competition. It seems there are significant technical hurdles that need to be overcome before these types of tools can reach the next level of precision and realism.
Other limitations are still in place, such as the inability to create images of famous people or generate content that violates Google's safety guidelines. Whether that's a good or a bad thing is a matter of opinion. For users seeking fewer restrictions, there are alternatives like Grok.
Have you tried out the latest image generation in Gemini? Let me know your thoughts in the comments.

Orange background

Try Our AI Features

Explore what Daily8 AI can do for you:

Comments

No comments yet...

Related Articles

The stablecoin evangelist: Katie Haun's fight for digital dollars
The stablecoin evangelist: Katie Haun's fight for digital dollars

TechCrunch

time43 minutes ago

  • TechCrunch

The stablecoin evangelist: Katie Haun's fight for digital dollars

In 2018, when Bitcoin was trading around $4,000 and most Americans, at least, thought cryptocurrency was a fad, Katie Haun found herself on a debate stage in Mexico City opposite Paul Krugman, the Nobel Prize-winning economist who had dismissed digital assets as near worthless. As Krugman focused on Bitcoin's wild price swings, Haun steered the conversation toward something else — stablecoins. 'Stablecoins are really interesting and really important to this ecosystem to hedge against that volatility,' she argued on stage, explaining how digital tokens pegged to the U.S. dollar could offer the benefits of blockchain technology without the volatility of traditional cryptocurrencies. Krugman dismissed the idea entirely. It wasn't exactly a turning point in Haun's career, but it was one moment among others that have helped define it. A former federal prosecutor who had spent more than a decade investigating financial crimes, including creating the government's first cryptocurrency task force and leading investigations into the Mt. Gox hack and corrupt agents in the Silk Road case, Haun had an unusual background for a crypto champion. She wasn't a libertarian ideologue or a tech founder. Coming instead from law enforcement, she understood the criminal potential and legitimate uses of digital assets. By 2018, she had already made history as the first female partner at Andreessen Horowitz, where she co-led their crypto funds. Founding Haun Ventures in 2022, with more than $1.5 billion in assets under management — its team is now investing from a brand-new set of funds that have yet to officially close — she has been even more free to pursue her specific convictions about the future of money. The leap to hanging her own shingle hasn't been without its complexities. Despite her role at a16z and the industry connections that came with it, the two haven't publicly co-invested in anything since early 2022, shortly after she launched her fund, and Haun, who joined the board of Coinbase in 2017, stepped off it last year, while Marc Andreessen, who took colleague Chris Dixon's seat in 2020, remains a director. When asked Wednesday night at TechCrunch's StrictlyVC event about her relationship with Andreessen Horowitz, she downplayed any potential friction while acknowledging they aren't collaborators exactly. 'There's no gentleman's agreement,' she said, echoing this editor's question about whether there's any understanding to avoid competing with her former employer. 'In fact, I still talk to Andreessen Horowitz. You're right that we haven't really done any deals together of late.' Techcrunch event Save $200+ on your TechCrunch All Stage pass Build smarter. Scale faster. Connect deeper. Join visionaries from Precursor Ventures, NEA, Index Ventures, Underscore VC, and beyond for a day packed with strategies, workshops, and meaningful connections. Save $200+ on your TechCrunch All Stage pass Build smarter. Scale faster. Connect deeper. Join visionaries from Precursor Ventures, NEA, Index Ventures, Underscore VC, and beyond for a day packed with strategies, workshops, and meaningful connections. Boston, MA | REGISTER NOW The apparent lack of co-investment could reflect the cutthroat industry or the challenges associated with leaving one of Silicon Valley's most prominent firms to compete directly with former colleagues. Whatever the case, Haun is now charting her own course, and at the heart of it is stablecoins, which are cryptocurrencies designed to maintain a stable value by being pegged to traditional assets like the U.S. dollar. Unlike Bitcoin or Ethereum, which can swing wildly in value, stablecoins like Circle's USDC or Tether's USDT are meant to trade at exactly $1, creating a digital representation of traditional currency that can move on blockchain networks. Indeed, fast-forward to today, and Haun's belief in stablecoins looks increasingly prescient. Stablecoins — which barely existed in 2015 — now represent a quarter of a trillion dollars in value. They've become the 14th largest holder of U.S. Treasuries globally, recently surpassing both Germany and Norway. For the first time this year, stablecoin transaction volume exceeded Visa's. 'I think people who looked at stablecoins a few years ago thought, what is the value prop?' Haun said Wednesday night. 'You've asked me this before. You said, 'Why do I need stablecoins?' And I said, 'I refer to this as an 'If it works for me, it works for everyone' problem.' In reality, for most Americans, the existing financial system works reasonably well. We have Venmo, bank accounts, credit cards. But Haun, drawing on her prosecutor's understanding of global financial systems, says she has long been aware that the U.S. experience isn't universal. In countries with unstable currencies or limited banking infrastructure, stablecoins offer something unique, she argues, which is instant access to stable, dollar-denominated value that can be sent anywhere in the world for pennies. 'People in Turkey don't think of Tether as a cryptocurrency,' she said Wednesday, 'They think of Tether as money.' The technology has evolved dramatically since those early debates, certainly. Stablecoins once cost $12 to send internationally. And Circle says its USDC stablecoin is fully backed one-to-one by dollars held in JP Morgan bank accounts and audited by Big Four accounting firms. It's important to note that while Circle and Tether are committed to having enough reserves to support their tokens, unlike traditional banks, there's no insured government protection behind these reserves. Still, the corporate world is taking notice in a big way. Walmart and Amazon are reportedly exploring stablecoins, as are other goliaths like Uber, Apple, and Airbnb. The reason is simple economics. Stablecoins provide a way to move the value of U.S. dollars using cryptocurrency rails instead of traditional banking infrastructure, potentially saving these retail-heavy companies billions in processing fees. But the shift has critics worried about economic chaos. If major corporations can issue their own currencies, what happens to monetary policy and banking regulation? The concerns run deeper than just economic disruption. Not all stablecoins are created equal, and many lack the backing and oversight that companies like Circle provide. While well-regulated stablecoins like USDC are backed by actual dollars in U.S. Treasury securities, others operate with less transparency or rely on complex algorithmic mechanisms that have proven vulnerable to collapse. (TerraUSD has had the most specular crash to date, wiping out $60 billion in value when it nosedived.) Corruption concerns in particular came into sharp focus recently when President Donald Trump's family issued its own stablecoin, a move that highlighted potential conflicts of interest in an industry where political influence can directly impact market value and regulatory outcomes. These concerns came to a head as Congress debated the GENIUS Act, legislation that would create a federal framework for stablecoin regulation. The bill passed the Senate early last week with bipartisan support, with 14 Democrats crossing party lines to support it. It now awaits a House vote before potentially reaching the president's desk. But Senator Elizabeth Warren, the ranking member on the Senate Banking Committee, has been particularly vocal in her opposition, calling the legislation a 'superhighway for Donald Trump's corruption.' Her criticism centers on a notable gap in the bill: while it prohibits members of Congress and senior executive branch officials from issuing stablecoin products, it says nothing about their family members. Asked about Warren's concerns on Wednesday night, Haun practically rolled her eyes. 'I think it's really ironic that Elizabeth Warren or other Democrats who do call this corruption are not running to pass crypto legislation,' she said. 'Had there been rules of the road in place [already], there would have been a framework, there would have been clear rules for what's a security, what's a commodity, and what are the consumer protections around that.' Haun, whose venture capital firm has made numerous stablecoin investments including Bridge (acquired by Stripe for reportedly 10 times forward revenue), is largely supportive of the legislation, unsurprisingly. But she has one notable criticism: the bill's prohibition on yield-bearing stablecoins. 'I'm not sure that yield-bearing stablecoins are a good idea for consumers in the U.S., but I'm not sure that a prohibition is a good idea,' she told StrictlyVC attendees. The issue comes down to who profits from the interest earned on stablecoin reserves. Currently, that money goes to companies like Circle and Coinbase. But Haun wonders why consumers shouldn't get that yield, just like they would with a savings account. 'If you had a savings account or checking account and you're getting yield on that, you're getting interest,' she explained. 'What if you just said, 'No, the bank gets interest, not you,' and they're lending out your money?' Haun was less nuanced when it comes to another Warren concern: that if the GENIUS Act is signed into law, stablecoins could become a vehicle for money laundering and terrorism financing. 'Criminals are great beta testers of all technologies,' said Haun. 'But this technology is highly traceable, way more traceable than cash. The largest criminal instrument is the dollar bill.' (According to Haun, the Treasury Department has testified that 99.9% of money laundering crimes succeed using traditional bank wires, not cryptocurrency.) Meanwhile, she said, the regulatory clarity that legislation like the GENIUS Act provides could actually make the system safer by distinguishing between legitimate, well-backed stablecoins from more experimental or risky variants. In fact, as the stablecoin ecosystem continues to mature, Haun sees even bigger changes ahead. She envisions a future where all kinds of assets — from money market funds to real estate to private credit — get 'tokenized' and made available 24/7 to global markets. 'It's just a digital representation of a physical asset,' she explains. 'BlackRock, Franklin Templeton, they've already tokenized their money market funds. That's already happened.' According to Haun, tokenized assets could democratize access to investments in ways similar to how Netflix democratized entertainment. Instead of having to be wealthy enough to meet minimum investment thresholds, someone with $25 and a smartphone could buy fractional ownership in a share of Apple or Amazon, for example. 'Just because something's inevitable doesn't mean it's imminent,' Haun said on Wednesday. But she's confident the transformation is coming, driven by the same forces that made stablecoins successful: they're faster, cheaper, and more accessible than traditional alternatives. Looking back at that 2018 debate with Krugman, Haun's persistence seems to have paid off. A major question now isn't whether digital dollars will reshape the financial system but perhaps more importantly, whether regulators can keep pace with the technology while addressing legitimate concerns about corruption, consumer protection, and financial stability. Haun doesn't seem concerned. While critics point to the fact that stablecoins represent just 2% of global payments, questioning their product-market fit, Haun sees this as a familiar tech adoption story — one that has played out repeatedly and often takes longer than people initially imagine. 'We think it's really early days,' she told the crowd.

From Cognitive Debt To Cognitive Dividend: 4 Factors
From Cognitive Debt To Cognitive Dividend: 4 Factors

Forbes

time44 minutes ago

  • Forbes

From Cognitive Debt To Cognitive Dividend: 4 Factors

Benjamin Franklin portrait and light bulbs idea concept on white background When an eye-catching (not yet peer reviewed) MIT Media Lab paper — Your Brain on ChatGPT — landed this month, the headline sounded almost playful. The data are anything but. Over four months, students who leaned on a large-language model to draft SAT-style essays showed the weakest neural connectivity, lowest memory recall, and flattest writing style of three comparison groups. The authors dub this hidden cost cognitive debt: each time we let a machine think for us, natural intelligence quietly pays interest. Is it time to quit the AI train while we still can, or this the moment to adopt a more thoughtful yet pragmatic alternative to blind offloading? We can deliberately offset cognitive debt with intentional mental effort, switching between solo thinking and AI-assisted modes to stretch neural networks rather than letting them atrophy. Drawing from insights into physiology, this might be the moment to adopt a cognitive high-intensity interval training. To get started think in terms of four sequential guardrails, the 4 A-Factors — that convert short-term convenience into the long-term dividend of hybrid Intelligence:. Attitude: Set The Motive Before You Type (Or Vibe Code) Mindset shapes outcome. In a company memo published on 17 June 2025, Amazon chief executive Andy Jassy urged employees to 'be curious about AI, educate yourself, attend workshops, and experiment whenever you can'. Curiosity can frame the system as a colleague rather than a cognitive crutch. Before opening a prompt window, write one sentence that explains why you are calling on the model, for example, 'I am using the chatbot to prototype ideas that I will refine myself.' The pause anchors ownership. Managers can reinforce that habit by rewriting briefs: swap verbs such as generate or replace for verbs that imply collaboration like co-design or stress-test. Meetings that begin with a shared intention end with fewer rewrites and stronger ideas. Approach: Align Aspirations, Actions And Algorithms Technology always follows incentives. If we measure only speed or click-through, that is what machines will maximize, often at the expense of originality or empathy. It does not have to be an either-or equation. MIT Sloan research on complementary capabilities highlights that pattern recognition is silicon's strength while judgment and ethics remain ours. Teams therefore need a habit of alignment. First, trace how a desired human outcome, i.e. say, customer trust, translates into day-to-day actions such as transparent messaging. Then confirm that the optimization targets inside the model rewards those very actions, not merely throughput. When aspirations, actions, and algorithms pull in one direction, humans stay in the loop where values matter and machines are tailored with a prosocial intention to accelerate what we value. Ability: Build Double Literacy Tools do not level the playing field; they raise the ceiling for those who can question them. An EY Responsible AI Pulse survey released in June 2025 reported that fewer than one-third of C-suite leaders feel highly confident that their governance frameworks can spot hidden model errors. Meanwhile an Accenture study shows that ninety-two per cent of leaders consider generative AI essential to business reinvention. The gap is interesting. Closing it requires double literacy: fluency in interpersonal, human interplays and machine logic. On the technical side, managers should know how to read a model card, notice spurious correlations, and ask for confidence intervals. On the human side, they must predict how a redesigned workflow changes trust, autonomy, or diversity of thought. Promotions and pay should reward people who speak both languages, because the future belongs to translators, not spectators. Ambition: Scale Humans Up, Not Out The goal is not to squeeze people out but to stretch what people can do. MIT Sloan's Ideas Made to Matter recently profiled emerging 'hybrid intelligence' systems that amplify and augment human capability rather than replace it.. Ambition reframes metrics. Instead of chasing ten-per-cent efficiencies, design for ten-fold creativity. Include indicators such as learning velocity, cross-domain experimentation, and employee agency alongside traditional return on investment. When a firm treats AI as a catalyst for human ingenuity, the dividend compounds: faster product cycles, richer talent pipelines, and reputational lift. 4 Quick Takeaways Attitude → Write the 'why' before the prompt; the pause keeps you in charge. Approach → Harmonize values and tools; adjust the tool when it drifts away from the values you believe in, as a human, offline. Not the other way → Learn to challenge numbers and narratives; double literacy begins with you. Ambition → Audit metrics quarterly to be sure they elevate human potential. Cognitive Debt Is Not Destiny Attitude steers intention, approach ties goals to code, ability equips people to question what the code does, and ambition keeps the whole endeavor pointed at humane progress. Run every digital engagement through the 4 A factor grid and yesterday's mental mortgage turns into tomorrow's dividend in creativity, compassion and shared humanistic value for all stakeholders.

Moratorium on state AI regulation clears Senate hurdle
Moratorium on state AI regulation clears Senate hurdle

Yahoo

timean hour ago

  • Yahoo

Moratorium on state AI regulation clears Senate hurdle

A Republican effort to prevent states from enforcing their own AI regulations cleared a key procedural hurdle on Saturday. The rule, as reportedly rewritten by Senate Commerce Chair Ted Cruz in an attempt to comply with budgetary rules, would withhold federal broadband funding from states if they try to enforce AI regulations in the next 10 years. And the rewrite seems to have passed muster, with the Senate Parliamentarian now ruling that the provision is not subject to the so-called Byrd rule — so it can be included in Republicans' 'One Big, Beautiful Bill' and passed with a simple majority, without potentially getting blocked by a filibuster, and without requiring support from Senate Democrats. However, it's not clear how many Republicans will support the moratorium. For example, Republican Senator Marsha Blackburn of Tennessee recently said, 'We do not need a moratorium that would prohibit our states from stepping up and protecting citizens in their state.' And while the House of Representatives already passed a version of the bill that included a moratorium on AI regulation, far-right Representative Marjorie Taylor Greene subbsequently declared that she is 'adamantly OPPOSED' the provision as 'a violation of state rights' and said it needs to be 'stripped out in the Senate.' House Speaker Mike Johnson defended the provision by saying it had President Donald Trump's support and arguing, 'We have to be careful not to have 50 different states regulating AI, because it has national security implications, right?' In a recent report, Americans for Responsible Innovation (an advocacy group for AI regulation), wrote that 'the proposal's broad language could potentially sweep away a wide range of public interest state legislation regulating AI and other algorithmic-based technologies, creating a regulatory vacuum across multiple technology policy domains without offering federal alternatives to replace the eliminated state-level guardrails.' A number of states do seem to be taking steps toward AI regulation. In California, Governor Gavin Newsom vetoed a high-profile AI safety bill last year while signing a number of less controversial regulations around issues like privacy and deepfakes. In New York, an AI safety bill passed by state lawmakers is awaiting Governor Kathy Hochul's signature. And Utah has passed its own regulations around AI transparency.

DOWNLOAD THE APP

Get Started Now: Download the App

Ready to dive into a world of global content with local flavor? Download Daily8 app today from your preferred app store and start exploring.
app-storeplay-store