How AI is Changing Advertising | IBM Watson Advertising Thought Leadership

AI-based advertising is transforming the marketing industry. Find out the benefits of applying artificial intelligence to your campaigns and how AI can help you create more personalized experiences for your target audience.

Like in so many industries, the use of data and AI is transforming advertising at a rapid pace. Consumers are seeing these changes in the personalized ads on their web browsers, the chatbots that help them make buying decisions. But what exactly is AI-powered advertising?

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Read the full article at: www.ibm.com

The end of the COVID pandemic is in sight, says WHO director

The world has never been in a better position to end the COVID-19 pandemic, the head of the World Health Organization said on Wednesday, urging nations to keep up their efforts against the virus has killed over six million people. “We are not there yet. But the end is in sight,” WHO Director-General Tedros Adhanom Ghebreyesus told reporters at a virtual press conference. The comment was the most optimistic from the UN agency since it declared the novel coronavirus an international emergency in January 2020 and started describing it as a pandemic in March 2020.

 

 

The virus, which emerged in China in late 2019, has killed nearly 6.5 million people and infected 606 million, roiling global economies and overwhelming healthcare systems. The rollout of vaccines and therapies has helped to stem the severity of the disease. Deaths from COVID-19 last week were the lowest since March 2020, the WHO reported. Still, countries need to take a hard look at their policies and strengthen them for COVID-19 and future viruses, Tedros said.  He also urged nations to vaccinate 100 per cent of their high-risk groups and keep testing for the virus.

 

The WHO warned of the possibility of future waves of the virus and said countries need to maintain adequate supplies of medical equipment and healthcare workers. “We expect there to be future waves of infections, potentially at different time points throughout the world caused by different subvariants of Omicron or even different variants of concern,” said WHO’s senior epidemiologist Maria Van Kerkhove. Monkeypox cases, too, were on a downtrend trend but Tedros urged countries to keep up the fight.

 

WHO officials said last month that it is possible to eliminate the monkeypox outbreak in Europe by stepping up vaccination and testing. “As with COVID-19, this is not the time to relax or let down our guard.”

Read the full article at: www.euronews.com

MIT’s MOXIE reliably produces oxygen on Mars

MIT’s MOXIE experiment has now produced oxygen on Mars. It is the first demonstration of in-situ resource utilization on the Red Planet, and a key step in the goal of sending humans on a Martian mission.

 

On the red and dusty surface of Mars, nearly 100 million miles from Earth, an instrument the size of a lunchbox is proving it can reliably do the work of a small tree. The MIT-led Mars Oxygen In-Situ Resource Utilization Experiment, or MOXIE, has been successfully making oxygen from the Red Planet’s carbon-dioxide-rich atmosphere since February 2021, when it touched down on the Martian surface as part of NASA’s Perseverance rover mission.

 

In a recently published study in the journal Science Advances, researchers report that, by the end of 2021, MOXIE was able to produce oxygen on seven experimental runs, in a variety of atmospheric conditions, including during the day and night, and through different Martian seasons. In each run, the instrument reached its target of producing six grams of oxygen per hour — about the rate of a modest tree on Earth. Researchers envision that a scaled-up version of MOXIE could be sent to Mars ahead of a human mission, to continuously produce oxygen at the rate of several hundred trees. At that capacity, the system should generate enough oxygen to both sustain humans once they arrive, and fuel a rocket for returning astronauts back to Earth.

 

So far, MOXIE’s steady output is a promising first step toward that goal. “We have learned a tremendous amount that will inform future systems at a larger scale,” says Michael Hecht, principal investigator of the MOXIE mission at MIT’s Haystack Observatory. MOXIE’s oxygen production on Mars also represents the first demonstration of “in-situ resource utilization,” which is the idea of harvesting and using a planet’s materials (in this case, carbon dioxide on Mars) to make resources (such as oxygen) that would otherwise have to be transported from Earth.

 

“This is the first demonstration of actually using resources on the surface of another planetary body, and transforming them chemically into something that would be useful for a human mission,” says MOXIE deputy principal investigator Jeffrey Hoffman, a professor of the practice in MIT’s Department of Aeronautics and Astronautics. “It’s historic in that sense.”

 

Hoffman and Hecht’s MIT co-authors include MOXIE team members Jason SooHoo, Andrew Liu, Eric Hinterman, Maya Nasr, Shravan Hariharan, and Kyle Horn, along with collaborators from multiple institutions including NASA’s Jet Propulsion Laboratory, which managed MOXIE’s development, flight software, packaging, and testing prior to launch.

 

Seasonal air

The current version of MOXIE is small by design, in order to fit aboard the Perseverance rover, and is built to run for short periods, starting up and shutting down with each run, depending on the rover’s exploration schedule and mission responsibilities. In contrast, a full-scale oxygen factory would include larger units that would ideally run continuously.

 

Despite the necessary compromises in MOXIE’s current design, the instrument has shown it can reliably and efficiently convert Mars’ atmosphere into pure oxygen. It does so by first drawing the Martian air in through a filter that cleans it of contaminants. The air is then pressurized, and sent through the Solid OXide Electrolyzer (SOXE), an instrument developed and built by OxEon Energy, that electrochemically splits the carbon dioxide-rich air into oxygen ions and carbon monoxide. The oxygen ions are then isolated and recombined to form breathable, molecular oxygen, or O2, which MOXIE then measures for quantity and purity before releasing it harmlessly back into the air, along with carbon monoxide and other atmospheric gases.

 

Since the rover’s landing in February 2021, MOXIE engineers have started up the instrument seven times throughout the Martian year, each time taking a few hours to warm up, then another hour to make oxygen before powering back down. Each run was scheduled for a different time of day or night, and in different seasons, to see whether MOXIE could accommodate shifts in the planet’s atmospheric conditions.

 

“The atmosphere of Mars is far more variable than Earth,” Hoffman notes. “The density of the air can vary by a factor of two through the year, and the temperature can vary by 100 degrees. One objective is to show we can run in all seasons.” So far, MOXIE has shown that it can make oxygen at almost any time of the Martian day and year.

 

“The only thing we have not demonstrated is running at dawn or dusk, when the temperature is changing substantially,” Hecht says. “We do have an ace up our sleeve that will let us do that, and once we test that in the lab, we can reach that last milestone to show we can really run any time.”

Read the full article at: news.mit.edu

Citizen Scientist Leads Discovery of 34 Ultracool Dwarf Binaries Using Just Archival Data

How often do stars live alone? For brown dwarfs — objects that straddle the boundary between the most massive planets and the smallest stars — astronomers need to uncover more examples of their companions to find out. Ace citizen scientist Frank Kiwy has done just that by using the Astro Data Lab science platform at NSF’s NOIRLab to discover 34 new ultracool dwarf binary systems in the Sun’s neighborhood, nearly doubling the number of such systems known.

 

A citizen scientist has searched NSF’s NOIRLab’s catalog of 4 billion celestial objects, known as NOIRLab Source Catalog DR2, to reveal brown dwarfs with companions. His intensive investigation led to the discovery of 34 ultracool dwarf binary systems, nearly doubling previously known samples [1].

 

Brown dwarfs lie somewhere between the most massive planets and the smallest stars. Lacking the mass needed to sustain nuclear reactions in their core, brown dwarfs loosely resemble cooling embers on a huge scale. Their faintness and relatively small sizes make them difficult to identify. Data from sensitive telescopes have enabled the discovery of several thousand objects but just a small subset have been identified as binaries. The difficulty in observing these faint embers also means that astronomers are still unsure how often brown dwarfs have companions.

 

Read the full article at: noirlab.edu

Pretrained diffusion models across multiple modalities using diffusers

https://github.com/huggingface/diffusers

 

Diffusers provides pretrained diffusion models across multiple modalities, such as vision and audio, and serves as a modular toolbox for inference and training of diffusion models.

More precisely, 🤗 Diffusers offers:

 

  • State-of-the-art diffusion pipelines that can be run in inference with just a couple of lines of code (see src/diffusers/pipelines). Check this overview to see all supported pipelines and their corresponding official papers.
  • Various noise schedulers that can be used interchangeably for the prefered speed vs. quality trade-off in inference (see src/diffusers/schedulers).
  • Multiple types of models, such as UNet, can be used as building blocks in an end-to-end diffusion system (see src/diffusers/models).
  • Training examples to show how to train the most popular diffusion model tasks (see examplese.g. unconditional-image-generation).

Read the full article at: colab.research.google.com

Just Released: Meet Lexica.art – A Massive Database Of AI-Generated Images 

If you’re one who’s looking for inspiration for your next AI-generated artwork, you should check out this website called Lexica.art. It’s a massive collection of millions of Stable Diffusion images including its text prompts people used to create them. The web app is pretty basic and neat with a simple discord link, a search box, and of course the images.

 

The way it’s described by the developer Sharif Shameem, is a search engine for AI-generated images and prompts. For instance, you can enter “astronaut” in the search box if you’re interested in seeing artworks related to an astronaut. What’s great is you’ll see the exact prompt used to generate the image on the left side. You can copy and remix these text prompts to create even cooler results. According to Sharif, Lexica is serving 100 GB of images per hour and is growing rapidly.

 

Lexica’s search engine is now 100% powered by CLIP. This means your search query will likely have thousands of matching Stable Diffusion images. You can also search by image similarity too.

 

God Mode

You can toggle the Grid Layout mode to quickly view hundreds of images on one page. Click on each photo to see the parameters like the prompt, seed, etc. You can even move the slider to change the size of the image previews. I like this mode better than the List view.

Read the full article at: medium.com

The Future is Here: AI-Generated Art Wins Art Prize – Artists Aren’t Happy

This year, the Colorado State Fair’s annual art competition gave out prizes in all the usual categories: painting, quilting and sculpture. But one entrant, Jason M. Allen of Pueblo West, Colorado, didn’t make his entry with a brush or a lump of clay. He created it with Midjourney, an artificial intelligence program that turns lines of text into hyper-realistic graphics. Mr. Allen’s work, “Théâtre D’opéra Spatial,” took home the blue ribbon in the fair’s contest for emerging digital artists — making it one of the first A.I.-generated pieces to win such a prize, and setting off a fierce backlash from artists who accused him of, essentially, cheating.

 

Reached by phone on Wednesday, Mr. Allen defended his work. He said that he had made clear that his work — which was submitted under the name “Jason M. Allen via Midjourney” — was created using A.I., and that he hadn’t deceived anyone about its origins.

 

“I’m not going to apologize for it,” he said. “I won, and I didn’t break any rules.” A.I.-generated art has been around for years and is here to stay. But tools released this year — with names like DALL-E 2, Midjourney and Stable Diffusion — have made it ultimately possible for rank amateurs to create complex, abstract or photorealistic works simply by typing a few words into a text box.

Read the full article at: www.nytimes.com

Top AI Papers Recommended by Experts

After the ‘top AI books’ reading list was so well received, we reached out to some of our community to find out which papers they believe everyone should have read!

All of the below papers are free to access and cover a range of topics from Hypergradients to modeling yield response for CNNs. Each expert also included a reason as to why the paper was picked as well as a short bio.

 

Part 1

Part 2

Read the full article at: blog.re-work.co