Get ready for the next generation of AI

You often can get better results by breaking generation down into multiple steps. For example, in the parachuting hippopotamus image above, I first prompted Photoshop to generate a hippo against a blue sky, then expanded the image to give it more sky, then added the parachute. But it also often produces distortions or weird problems – for example, an elephant with a second trunk where its tail should be. Often you’ll have to reject a lot of Firefly duds and try different prompts to get useful results, and so far at least, it doesn’t look likely that MidJourney fans will abandon that rival tool for generating AI imagery. In my testing, Firefly often was able to capably blend imagery with existing scenes, either inserting elements with the generative fill tool or widening an image with generative expand. It sometimes can match a scene’s lighting and perspective, a difficult feat, and even create plausible reflections.

As other models are implemented, Adobe will continue to prioritize countering potential harmful bias. Additionally, 60% of respondents do not anticipate generative AI to alleviate the talent shortage in the gaming industry significantly. The 60% figure is a big deal, as it could mean that generative AI won’t necessarily wipe out a ton of jobs, the executives believe.

Salesforce Artificial Intelligence

It’s impressive — there’s minimal flickering, the styling is consistent across frames, and the frame interpolation is very smooth. Response rates for such ads are demonstrably higher than conventional, non-personalized equivalents. This level of personalization and customization fosters customer loyalty, which benefits the client and the company. They experience less churn and do a better job of generating more revenue from each client. AI’s strength is taking large volumes of information, picking out important points, correlating them and helping employees glean new knowledge. Bain & Company, a global consultancy firm, helps organizations drive transformative change.

In the near future, we expect applications that target specific industries and functions will provide more value than those that are more general. Users are betting that the platform is going to become a less fun place to hang out. That’s partly because they’ve seen Musk laying off teams of people who work to make sure the platform is safe, including Twitter’s entire AI ethics team. But we can only wonder what damage has been done already, especially with the US midterm elections imminent.

ChatGPT prompts

There are AI techniques whose goal is to detect fake images and videos that are generated by AI. The accuracy of fake detection is very high with more than 90% for the best algorithms. But still, even the missed 10% means millions of fake contents being generated and published that affect real people. Firefly, Express Premium and Creative Cloud paid plans now
include an allocation of Generative Credits. Adobe Firefly-powered features are now available in several Creative Cloud apps, including Generative Fill and Generative Expand in Photoshop, Generative Recolor in Illustrator and Text to Image and Text Effects in Adobe Express. These native integrations deliver more creative power than ever before to customers, empowering them to experiment, ideate and create in completely new ways.

• In our case we did an interview with AI and it sounded really interesting and natural.
• Two scenarios are shown for early and late adoption of automation, and each bar is broken into the effect of automation with and without generative AI.
• After testing it with 1,000 financial advisers for some months, the bank will roll out a generative artificial intelligence bot this month, developed with the makers of ChatGPT, OpenAI.
• The cost of generating images, 3D environments and even proteins for simulations is much cheaper and faster than in the physical world.
• They knew that if they didn’t nail safety, everyone would be scared and they would lose business.

Within the technology’s first few months, McKinsey research found that generative AI (gen AI) features stand to add up to $4.4 trillion to the global economy—annually. Essentially, it’s about setting boundaries, limits that an AI can’t cross. And ensuring that those boundaries create provable safety all the way from the actual code to the way it interacts with other AIs—or with humans—to the motivations and incentives of the companies creating the technology.

Yakov Livshits
Founder of the DevEducation project
A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.

And by this time next year the world and its attendant conflicts will have moved on yet again as today’s models and methods are abandoned. The cost of generating images, 3D environments and even proteins for simulations is much cheaper and faster than in the physical world. One is generating (for instance images) while  the second Yakov Livshits is verifying the results, for instance if the images are natural and look true. NVIDIA announced a new ML based method for compressing video called Maxine used for teleconferences, that reduces the required bandwidth more than ten times, in other words, it enables ten times more people to attend the conference at the same time.

Gen AI is a big step forward, but traditional advanced analytics and machine learning continue to account for the lion’s share of task optimization, and they continue to find new applications in a wide variety of sectors. Organizations undergoing digital and AI transformations would do well to keep an eye on gen AI, but not to the exclusion of other AI tools. Just because they’re not making headlines doesn’t mean they can’t be put to work to deliver increased productivity—and, ultimately, value. But like any new technology, gen AI doesn’t come without potential risks. For one thing, gen AI has been known to produce content that’s biased, factually wrong, or illegally scraped from a copyrighted source. Before adopting gen AI tools wholesale, organizations should reckon with the reputational and legal risks to which they may become exposed.

Deploy AI with Ethics by Design, intentionally embedding ethical and humane use guiding principles in the design, development, and delivery of software. Equip Einstein Copilot with a menu of AI-powered, domain-specific actions that it can mix and match based on your customer’s needs. I used Photoshop’s Firefly generative AI technology to add this red crab to a photo I took of an American avocet sweeping a mudflat with its bill. Firefly is smart enough to get the crab’s reflection mostly right, though if you look closely, imperfections are evident. UBS analyst Karl Keirstead estimated in a report Thursday that Adobe will generate $400 million to $500 million in new revenue from the price increase in the company’s next fiscal year. He had expected Adobe to charge for a standalone Firefly subscription, though, not to have it folded into the overall Creative Cloud prices.

“There is a question of IP ownership that’s being tackled within AI applications across all industries, not just gaming. And I think the feeling is that these are solvable issues in the near to medium Yakov Livshits term. And there’ll be legal processes that will enable video game companies to be able to use AI for sure,” he said. Some have pointed out the legal and regulatory challenges of the work.

Adobe will continuously bring Firefly-powered features into more Creative Cloud apps and workflows for photography, imaging, illustration, design, video, 3D and beyond. Corporations have complex business processes designed to create products, serve customers and comply with industry regulations. Applications of AI have the power to automate repetitive tasks, reduce manual input and boost productivity. Zoom announced several new capabilities coming to Revenue Accelerator, including a “virtual coach” to simulate conversations for onboarding and training sales team members.

In a continuation of current trends, Google announced a slew of advances in generative AI, including a system that combines its two text-to-video AI models, Phenaki and Imagen. Phenaki allows the system to generate video with a series of text prompts that functions as a sort of script, while Imagen makes the videos higher resolution. This sounds like magic — and indeed, it doesn’t exist yet — but it would be just an ensemble of three AI programs.

Gen AI’s precise impact will depend on a variety of factors, such as the mix and importance of different business functions, as well as the scale of an industry’s revenue. Nearly all industries will see the most significant gains from deployment of the technology in their marketing and sales functions. But high tech and banking will see even more impact via gen AI’s potential to accelerate software development. If it works out, this will represent a big leap forward in the capabilities of large language models, or LLMs. AI startup Hugging Face’s LLM BLOOM was trained on 46 languages, and Meta has been working on AI models that can translate hundreds of languages in real time. With more languages contributing training data to its model, Google will be able to offer its services to even more people.