Meta AI has been integrated into WhatsApp for some time, but users must currently type their queries. According to WABetaInfo, an upcoming release will reduce the barrier to entry, giving users the option to send a voice message instead.

The ability to share voice messages with Meta AI allows for quicker communication, as speaking is generally faster than typing. This can be particularly useful for users who need to share information or ask questions on the go. Thanks to Meta AI’s advanced speech recognition technology, the AI chatbot can accurately understand the content of voice messages, ensuring that users’ queries are comprehended and addressed effectively. In cases where Meta AI cannot understand the content of a voice message, perhaps due to background noise or poor audio quality, the chatbot will prompt users to record the message again. This ensures that communication always remains clear and effective, maintaining a high standard of user experience and interaction with the AI.

The feature builds on capabilities WABetaInfo already reported on that demonstrate how effective an assistant Meta is aiming to provide.

Through this enhancement, users will be able to interact with their photos in new ways by asking Meta AI questions about the content in the future, such as identifying objects or providing context. Additionally, users will have the ability to make quick edits and adjustments to their photos directly within the chat. It seems that WhatsApp is now dedicated to introducing additional features for Meta AI, with the aim to enhance interactions with the chatbot.

The description sounds similar to what OpenAI showed off when it debuted GPT-4o, with an emphasis on voice and contextual interaction.

Given that WhatsApp is the most popular messaging platform on the planet, Meta has every motivation to make its Meta AI as accessible as possible. Doing so could give the company a leg up in the AI wars, allowing it to tap into its vast user base to drive AI adoption.

AI is the hottest trend in the tech industry, with proponents saying it is poised to revolutionize virtually every possible corner of the market. Despite the enthusiasm, the financial market is growing increasingly weary of AI, seeing a technology that is has become a money pit with little real-world potential for a return.

In a memo to investors, seen by Financial Times, via Investing.com, Elliot said that AI is overhyped with many applications not ready for prime time.” The memo goes on to say that AI has “few real uses” aside from “summarising notes of meetings, generating reports and helping with computer coding,” is fundamentally software that has yet to return a “value commensurate with the hype.”

Elliot did not paint a much better picture for the future, saying AI apps are “never going to be cost-efficient, are never going to actually work right, will take up too much energy, or will prove to be untrustworthy.”

Golman Sach issued a report in early July, with some of its analysts reaching similar conclusions.

GS Head of Global Equity Research Jim Covello minced no words in his evaluation of AI:

Many people attempt to compare AI today to the early days of the internet. But even in its infancy, the internet was a low-cost technology solution that enabled e-commerce to replace costly incumbent solutions. Amazon could sell books at a lower cost than Barnes & Noble because it didn’t have to maintain costly brick-and-mortar locations. Fast forward three decades, and Web 2.0 is still providing cheaper solutions that are disrupting more expensive solutions, such as Uber displacing limousine services. While the question of whether AI technology will ever deliver on the promise many people are excited about today is certainly debatable, the less debatable point is that AI technology is exceptionally expensive, and to justify those costs, the technology must be able to solve complex problems, which it isn’t designed to do.

Reports have been growing that investors are growing weary of AI as concerns grow about its future while its price tag keeps growing. With names like Goldman Sachs and Elliot Management warning of an AI bubble, the tech industry could be poised for a major adjustment.

Deepfake porn has been a growing problem, especially with the rise of AI. The technology has made deepfakes so convincing that it can be almost impossible to tell if a deepfake is real or not. As a result, victims often deal with emotional damage and humiliation, not to mention damage to the victim’s reputation if the deepfake is widely circulated without people realizing it’s fake.

According to Engadget, the US Senate aims to tackle the problem with the Disrupt Explicit Forged Images and Non-Consensual Edits Act (DEFIANCE Act). The bill would give victims 10 years to sue for damages.

The DEFIANCE Act would give victims the ability to sue not only those who create nonconsensual deepfake porn, but also those who distribute and possess such material. Initial damages could be up to $150,000, with that figure going up to $250,000 if the incident also includes stalking, harassment, or attempted sexual assault.

Majority Leader Chuck Schumer praised the passage of the bill in his remarks in his floor remarks:

As we know, AI plays a bigger role in our lives than ever before, and while it has many benefits, it’s also easier than ever to create sexually explicit deep fakes without a person’s consent. It is a horrible attack on someone’s privacy and dignity to have these fake images of them circulating online without recourse.

And this isn’t just some fringe issue that happens to only a few people—it’s a widespread problem. These types of malicious and hurtful pictures can destroy lives. Nobody is immune, not even celebrities like Taylor Swift or Megan Thee Stallion. It’s a grotesque practice and victims of these deep fakes deserve justice. And this is one of the examples of the AI guardrails I often talk about. AI is a remarkable technology that can spur incredible innovation, but we must pass guardrails to prevent its worst abuses from causing people grave harm.

By passing this bill, we are telling victims of explicit nonconsensual deepfakes that we hear them and we are taking action.

The House will likely vote on a sister bill. If it passes the house, it will go to President Biden to be signed into law.

Wiens took to X to ask Anthropic to stop crawling the iFixit website:

Hey @AnthropicAI: I get you’re hungry for data. Claude is really smart! But do you really need to hit our servers a million times in 24 hours?

You’re not only taking our content without paying, you’re tying up our devops resources. Not cool.

Kyle Wiens (@kwiens) | July 24, 2024

Wiens goes on to say that iFixit’s TOS expressly forbid AI crawlers from scraping its content, and the TOS was in effect before Anthropic began scraping the site. iFixit has since added Anthropic to its robots.txt file, but it remains to be seen if Anthropic will respect it.

Wiens post raises a number of concerning issues:

• It is inexcusable that an AI company trying to set itself apart as the responsible company in an industry beset with ethics issues is blatantly ignoring other companies’ TOS in order to grab content.
• It is even more inexcusable that Anthropic’s crawler is hitting any one company’s “servers a million times in 24 hours.” Such behavior has more in common with malicious DDoS attacks than it does legitimate activity.

Unfortunately, iFixit’s experience is far from unique. Read the Docs cofounder Eric Holscher responded to Wiens to say his organization had experienced the same thing:

Yea, they were hammering us over at @readthedocs as well. We were planning to write a blog post on it, since this behavior is definitely gonna get all AI crawlers blocked because of abuse, not even because of the copyright issues.

Eric Holscher (@ericholscher) | July 24, 2024

Several other individuals from well-known organizations—such as Wikipedia and PythonAnywhere—reported similar behavior from AI firms.

iFixit’s experience illustrates why so many people don’t trust AI companies. Such companies are playing fast and loose with the ethics of content ownership, not to mention creating a very real burden on the organizations whose content they are accessing. Rather than acting responsibly, AI companies are in a mad dash to vacuum up as much data as possible before legislation properly regulates the industry.

Hopefully Anthropic will do the right thing and adjust its policies in the wake of iFixit’s revelation.

With the rise of AI, datacenters are in high demand. Microsoft is tapping Lumen to help it expand its datacenter infrastructure, increasing both capacity and capability.

The company explains in a blog post:

Datacenters have become critical infrastructure that power the compute capabilities for the millions of people and organizations who rely on and trust the Microsoft Cloud. Microsoft is playing a leading role in ushering in the era of AI, offering tools and platforms like Azure OpenAI Service, Microsoft Copilot and others, to help people be more creative, more productive and to help solve some of humanity’s biggest challenges. As Microsoft continues to evolve and scale its ecosystem, it is turning to Lumen as a strategic supplier for its network infrastructure needs and is investing with Lumen to support its next generation of applications for Microsoft platform customers worldwide.

Lumen’s Private Connectivity Fabric℠ is a custom network that includes dedicated access to existing fiber in the Lumen network, the installation of new fiber on existing and new routes, and the use of Lumen’s new digital services. This AI-ready infrastructure will strengthen the connectivity capabilities between Microsoft’s datacenters by providing the network capacity, performance, stability and speed that customers need as data demands increase.

“AI is reshaping our daily lives and fundamentally changing how businesses operate,” said Erin Chapple, corporate vice president of Azure Core Product and Design, Microsoft. “We are focused both on the impact and opportunity for customers relative to AI today, and a generation ahead when it comes to our network infrastructure. Lumen has the network infrastructure and the digital capabilities needed to help support Azure’s mission in creating reliable and scalable platform that supports the breadth of customer workloads—from general purpose and mission-critical, to cloud-native, high-performance computing, and AI, plus what’s on the horizon. Our work with Lumen is emblematic of our investments in our own cloud infrastructure, which delivers for today and for the long term to empower every person and every organization on the planet to achieve more.”

“We are preparing for a future where AI is the driving force of innovation and growth, and where a powerful network infrastructure is essential for companies to thrive,” said Kate Johnson, president and CEO, Lumen Technologies. “Microsoft has an ambitious vision for AI and this level of innovation requires a network that can make it reality. Lumen’s expansive network meets this challenge, with unique routes, unmatched coverage, and a digital platform built to give companies the flexibility, access and security they need to create an AI-enabled world.”

In turn, Lumen will migrate its workloads to Microsoft Azure, using the cloud provider to remove legacy system, breakdown silos, and modernize its services. The companies estimate this will “improve Lumen’s cash flow by more than $20 million over the next 12 months,” while also helping the company improve the service it provides to its customers.

“Azure’s advanced global infrastructure helps customers and partners quickly adapt to changing economic conditions, accelerate technology innovation, and transform their business with AI,” said Chapple. “We are committed to partnering with Lumen to help deliver on their transformation goals, reimagine cloud connectivity and AI synergies, drive business growth, and help customers achieve more.”

TechPowerUp conducted a poll of its readers to see how many were willing to pay more for computer hardware with AI capabilities. Interestingly, with nearly 27,000 users voting in the poll, a whopping 84.1% were unwilling to pony up for AI-powered hardware. Another 8.6% said they were unsure, with only 7.3% willing to pay more.

Among the issues users highlighted for their reluctance to pay more is the lack of interesting uses for AI other than creating images. Others voiced concerns with AI models that require user data to be sent to data centers for processing, saying they would be far more willing to pay for AI-powered hardware when that hardware is powerful enough to run the AI models locally.

Still others felt that paying for AI-powered hardware is simply premature, with genuinely useful hardware still several generations away.

One user, Steevo, had one of the most critical responses, saying they would be willing to pay more to have AI hardware removed in favor of more cache or other useful hardware options.

The poll is telling insight into the state of the industry at a time when all the major chipmakers are rushing to implement AI-specific hardware in their designs, all in the hope that users are willing to pay such features.

Experts have begun to warn that the AI revolution may be shaping up to be more like an AI bubble. Goldman Sachs recently warned that “the technology isn’t designed to solve the complex problems that would justify the costs.”

If the AI bubble bursts, it could be devastating to semiconductor and PC makers.

Apple announced in June that it would not bring its Apple Intelligence features to the EU as a result of concerns over the Digital Markets Act (DMA). At the time, Apple made the following statement:

Due to the regulatory uncertainties brought about by the Digital Markets Act, we do not believe that we will be able to roll out three of these [new] features — iPhone Mirroring, SharePlay Screen Sharing enhancements, and Apple Intelligence — to our EU users this year.

Meta is following suit, saying in a statement to Axios that it has no intention of bringing its multimodal AI models to the EU, citing the same uncertainty.

We will release a multimodal Llama model over the coming months, but not in the EU due to the unpredictable nature of the European regulatory environment.

In addition to not bringing the AI models to the EU directly, Meta told Axios that EU companies will not be able to use the models, despite the fact that they are open source.

As the outlet points out, the UK has similar legislation as the EU, but neither Apple nor Meta have refused to roll out AI there. Meta chalked this up to EU regulators taking much longer to interpret and apply regulation to specific cases, meaning companies are in limbo much longer and risk higher fines once a decision is eventually reached.

The EU has been aggressively moving to regulate Big Tech, but is already experiencing significant push-back. Critics have accused EU regulators of trying to turn Apple’s iOS into another Android, rather than letting the two ecosystems compete against each other on their own unique merits—one walled off and protected, the other more open and free.

With companies now deciding to not bring technology to the EU—and with there being no legal requirement or ability to force companies to do so—regulators will need to decide if the bloc’s measures are backfiring. If companies refuse to bring advanced tech to the EU, the bloc could quickly find itself at a competitive disadvantage, compared to the rest of the world.

The Relentless Demand for AI Infrastructure

CoreWeave’s CEO noted the skyrocketing demand for AI infrastructure. “The market that we’re seeing and we are very close to the true demand for this infrastructure is relentless,” Intrator stated. “It’s been in a state of severe disequilibrium for the past 2 1/2 years.” He emphasized that the demand shows no signs of slowing down, with clients consistently planning their needs far into the future.

CoreWeave’s planning cycles reflect this high demand, with some companies looking for a year. “They’re basically pinned because we don’t have enough capacity to be able to train our models or serve them through inference,” Intrator explained. The company’s unique capability to deliver infrastructure at the required scale has positioned it as a key player in the AI landscape. “We are one of the few companies in the world that can bring on this kind of infrastructure at the scale that’s required to actually make a difference,” he added.

Managing Risks in a Rapidly Growing Market

Despite the booming market, Intrator acknowledged the inherent risks of overexpansion. “We’re a small company competing against giants, and the consequences of getting out too far over your skis can be catastrophic,” he noted. To mitigate these risks, CoreWeave focuses on “the long poles” such as building physical infrastructure and securing necessary resources like mid-voltage transformers and power. These elements take considerable time to deliver but are essential for the company’s long-term strategy.

The company’s client-driven approach further limits exposure. By allowing clients to request capacity, CoreWeave ensures that its investments are aligned with actual demand. “Our exposure is limited to the long poles,” Intrator reiterated, highlighting the company’s cautious yet strategic expansion approach. “The way that we handle our clients is that they come in and they request capacity from us,” he explained. “This helps us manage our risks effectively.”

The Challenge of Accessing AI Chips

One of the critical challenges in the AI industry is securing access to the necessary chips. Intrator discussed how timelines for chip access are governed by two main factors: the release of new chip generations and the availability of physical infrastructure to support increased compute capacity. “The timelines for access to the chips are being governed by new generations of chips that are coming out and the capacity to be able to have enough physical infrastructure to bring that compute online,” he said.

When asked about the influence of political shifts, such as comments from former President Trump, Intrator was clear that market dynamics and infrastructure capacity are the primary drivers of chip availability. “Political factors can certainly play a role, but the primary drivers are the release of new chip generations and the capacity to support them,” he emphasized.

CoreWeave’s Commitment to NVIDIA Technology

Intrator confirmed that the company primarily delivers what its clients demand, which is overwhelmingly NVIDIA’s hardware. “We allow our clients to lead us,” he said. We are one of the true resources for the delivery of NVIDIA’s infrastructure.”

While CoreWeave evaluates different types of silicon-based on performance, the client preference for NVIDIA is clear. “Overwhelmingly, our clients want NVIDIA technology,” Intrator noted, emphasizing the company’s commitment to meeting this demand despite exploring other potential silicon options. “Our clients may be self-selecting, knowing that we are good with NVIDIA technology and bringing it to us for their builds,” he added.

The Future of AI Infrastructure and Energy Consumption

As the demand for AI chips and infrastructure continues to grow, the energy required to power these systems has become a crucial consideration. Intrator addressed concerns about the long-term sustainability of AI infrastructure, particularly regarding energy consumption and processing power. “We think about this a lot,” he said. “We try to focus on securing the necessary resources to ensure that we can support the growing demand without overextending ourselves.”

CoreWeave aims to build a resilient and sustainable AI infrastructure by focusing on long-term planning and client-driven capacity requests. “We are taking a strategic approach to ensure that we can continue to meet demand without compromising on our core principles of sustainability and efficiency,” Intrator stated.

Looking Ahead: CoreWeave’s Growth and Industry Impact

CoreWeave’s rapid expansion and strategic planning have positioned it as a formidable competitor in the AI infrastructure market. The company’s focus on client needs and its cautious yet ambitious growth strategy reflects a broader trend in the tech industry towards specialized, scalable solutions for AI applications. “We are not just meeting current demand; we are paving the way for future advancements in AI technology,” Intrator said.

As CoreWeave continues to build data centers across the United States and Europe, the startup is meeting current demand and preparing for future growth. “We are building a foundation to support the next generation of AI applications,” Intrator concluded. His insights underscore the dynamic nature of the AI industry and the critical role that infrastructure providers like CoreWeave play in its evolution.

With AI applications set to become even more integral to various sectors, CoreWeave’s strategic approach and focus on delivering high-performance infrastructure will likely keep it at the forefront of the industry. As Intrator aptly put it, “We are one of the few companies in the world that can bring on this kind of infrastructure at the scale that’s required to actually make a difference.”

The issue was discovered by Kevin Bankston, Senior Advisor on AI Governance at the Center for Democracy & Technology. Bankston first noticed the issue when he realized Gemini had summarized his tax return, with being asked to.

Just pulled up my tax return in @Google Docs–and unbidden, Gemini summarized it. So…Gemini is automatically ingesting even the private docs I open in Google Docs? WTF, guys. I didn’t ask for this. Now I have to go find new settings I was never told about to turn this crap off.

Kevin Bankson (@KevinBankston) | July 10, 2024

In a long X thread, Bankston continued investigating what was happening, why Gemini had accessed his tax return, and how to turn the feature off. Needless to say, his experience is not reassuring. After searching and failing to find a setting that would prevent Gemini from accessing his private documents, Bankston asked Gemini to point him in the right direction—only to find that neither of Gemini’s suggestions worked.

Ultimately another user was able to point Bankston to Gemini Workspace privacy commitments that make it clear the AI doesn’t use inputted data for training. As Bankston points out, however, that still doesn’t settle the issue of being in control of one’s own data and prohibiting Gemini from accessing it all.

Bankston has some strong words for Google’s decision makers.

If this was a deliberate choice rather than some screwup, I can pretty clearly imagine the internal arguments that went into this very, very wrong @Google decision. So I’ll just say: listen a bit more to your privacy and responsibility people and a bit less to your growth people.

Kevin Bankston (@KevinBankston) | July 10, 2024

Bankston’s case is a damning indictment of Google—and the AI industry at large—and the reckless, irresponsible way such companies are addressing issues surrounding user privacy.

Google’s Response

Google reached out to WPN to emphasize that the company does not use Workspace data for training purposes, and no data is “ingested.” The company insists that any summaries are being done in real time, with no summaries or information from the document itself stored.

“Our generative AI features are designed to give users choice and keep them in control of their data. Using Gemini in Google Workspace requires a user to proactively enable it, and when they do their content is used in a privacy-preserving manner to generate useful responses to their prompts, but is not otherwise stored without permission.” – a Google spokesperson 

There is still no word on whether the company plans to give users the ability to exclude specific content entirely, for those who want more granular control over what Gemini accesses—regardless of how that access occurs.

The EU passed one of the most comprehensive pieces of legislation aimed at regulating how AI can and cannot be used. Per the bloc’s rules, once a piece of legislation is published in the Official Journal, it becomes enforceable 20 days later.

First spotted by TechCrunch, the EU AI Act was published in the Official Journal Friday, meaning August 1 is the day it initially goes into effect. As the outlet points out, the legislation has a phased rollout, meaning that some provisions won’t apply until mid-2026, and some even later than that.

Nonetheless, AI firms should take note that August 1 represents a fundamental change in how AI will be governed in the EU.

AI models require massive amounts of data for training purposes, with many of those models trained on content that is available on the internet. The ethics of the practice are among the most hotly debated topics in the industry, with multiple lawsuits attempting to settle the questions.

The COPIED Act—introduced by Senators Maria Cantwell, Marsha Blackburn, and Martin Heinrich—would protect journalists, actors, artists, and songwriters, giving them control over their content. The COPIED Act provides four distinct protections:

• Creates Transparency Standards: Requires the National Institute of Standards and Technology (NIST) to develop guidelines and standards for content provenance information, watermarking, and synthetic content detection. These standards will promote transparency to identify if content has been generated or manipulated by AI as well as where AI content originated. The bill also directs NIST to develop cybersecurity measures to prevent tampering with provenance and watermarking on AI content.
• Puts Journalists, Artists, and Musicians in Control of Their Content: Requires providers of AI tools used to generate creative or journalistic content to allow owners of that content to attach provenance information to it and prohibits its removal. The bill prohibits the unauthorized use of content with provenance information to train AI models or generate AI content. These measures give content owners—journalists, newspapers, artists, songwriters, and others—the ability to protect their work and set the terms of use for their content, including compensation.
• Gives Individuals a Right to Sue Violators: Authorizes the Federal Trade Commission (FTC) and state attorneys general to enforce the bill’s requirements. It also gives newspapers, broadcasters, artists, and other content owners the right to bring suit in court against platforms or others who use their content without permission.
• Prohibits Tampering with or Disabling AI Provenance Information: Currently, there is no law that prohibits removing, disabling, or tampering with content provenance information. The bill prohibits anyone, including internet platforms, search engines, and social media companies, from interfering with content provenance information in these ways.

“The bipartisan COPIED Act I introduced with Senator Blackburn and Senator Heinrich, will provide much-needed transparency around AI-generated content,” said Senator Cantwell. “The COPIED Act will also put creators, including local journalists, artists and musicians, back in control of their content with a provenance and watermark process that I think is very much needed.”

“Artificial intelligence has given bad actors the ability to create deepfakes of every individual, including those in the creative community, to imitate their likeness without their consent and profit off of counterfeit content,” continued Senator Blackburn. “The COPIED Act takes an important step to better defend common targets like artists and performers against deepfakes and other inauthentic content.”

“Deepfakes are a real threat to our democracy and to Americans’ safety and well-being,” added Senator Heinrich. “I’m proud to support Senator Cantwell’s COPIED Act that will provide the technical tools needed to help crack down on harmful and deceptive AI-generated content and better protect professional journalists and artists from having their content used by AI systems without their consent. Congress needs to step up and pass this legislation to protect the American people.”

If the COPIED Act passes and is signed into law, it will revolutionize the AI industry and finally provide journalists and creatives the protections they need.

Graphcore specializes in SoIC-WoW (Wafer–on-Wafer) IPUs (intelligence processing units), designed to compete against the industry-standard GPUs that power AI models. The company says its IPUs offer significant benefits over traditional GPUs.

The IPU is a completely new kind of massively parallel processor, co-designed from the ground up with the Poplar® SDK, to accelerate machine intelligence.

The compute and memory architecture are designed for AI scale-out. The hardware is developed together with the software, delivering a platform that is easy to use and excels at real-world applications.

Graphcore co-founder and CEO Nigel Toon says his company has joined SoftBank, but will be a wholly owned SoftBank subsidiary, but Will continue to remain headquartered in Bristol and operate under the Graphcore name.

“This is a tremendous endorsement of our team and their ability to build truly transformative AI technologies at scale, as well as a great outcome for our company,” said Graphcore co-founder and CEO Nigel Toon. “Demand for AI compute is vast and continues to grow. There remains much to do to improve efficiency, resilience, and computational power to unlock the full potential of AI. In SoftBank, we have a partner that can enable the Graphcore team to redefine the landscape for AI technology.”

“Society is embracing the opportunities offered by foundation models, generative AI applications and new approaches to scientific discovery”, said Vikas J. Parekh, Managing Partner at SoftBank Investment Advisers. “Next generation semi-conductors and compute systems are essential in the AGI journey, we’re pleased to collaborate with Graphcore in this mission.”

The deal already has regulatory approval. The decision for Graphcore to continue operating from the UK under its own name may have played a part in winning regulatory approval. Critics in the UK have previously voiced concern that the UK could lose control of its semiconductor industry, with those concerns being a factor in the UK opposing Nvidia’s attempt to purchase Arm Holdings.

SoftBank being the buyer likely played a role in regulatory approval as well, since SoftBank owned Arm before it went public. Much like Graphcore, Arm had the freedom to operate largely independently, and maintained its headquarters in the UK.

The financial terms of the deal were not disclosed.

AMD has been working to build out its software offerings, an attempt to grow beyond its core chip business and challenge Nvidia in the broader AI market. Silo AI has experience scaling large language models, building custom AI solutions, and serving the cloud, embedded, and endpoint markets.

“Silo AI has been a pioneer in scaling large language model training on LUMI, Europe’s fastest supercomputer powered by over 12,000 AMD Instinct MI250X GPUs,” said Dr. Pekka Manninen, Director of Science and Technology at CSC-IT Center for Science, Finland. “Together with university collaborators, they have trained state-of-the-art open-source models for EU languages, such as the Nordic Poro and Viking models. We have collaborated extensively with the team in optimizing the software layer, allowing for efficient training of AI models on LUMI.”

Silo AI co-founder and CEO Peter Sarlin said joining forces with AMD is the next logical step for the Finnish company.

“At Silo AI, our mission from the start has been to build an AI flagship company. Today’s announcement is a logical next step in that pursuit as we join forces with AMD to shape the future of AI computing,” said Peter Sarlin, CEO and co-founder of Silo AI. “We have a well-established history of building successful AI products and delivering value to our customers. We look forward to becoming part of AMD to further scale our impact and develop enterprise solutions and AI models that address the most complex challenges with deploying AI at scale today.”

AMD said Sarlin will continue to lead Silo AI as the company joins the AMD Artificial Intelligence Group.

“Across every industry, enterprises are looking for fast and effective ways to develop and deploy AI solutions for their unique business needs,” said Vamsi Boppana, senior vice president of the Artificial Intelligence Group at AMD. “Silo AI’s team of trusted AI experts and proven experience developing leadership AI models and solutions, including state-of-the-art LLMs built on AMD platforms, will further accelerate our AI strategy and advance the build-out and rapid implementation of AI solutions for our global customers.”

The transaction is an all-cash deal, worth approximately $665 million.

Why Removing Backgrounds is Necessary

For commercial websites and catalogs, the presentation of product images is crucial. Here are a few reasons why background removal is essential:

• Focus on Product

By removing distracting surroundings, the product becomes the focal point of the image. This helps customers see the details and features clearly and make purchasing decisions easily.

• Consistency 

A uniform background across all product images creates a cohesive and professional look for your online store. This consistency builds trust and enhances brand recognition.

• Versatility

Background-free pictures can be easily integrated into various marketing materials, such as advertisements, banners, and social media posts, without clashing with other design elements.

• Improved Load Times

Simplified photos with plain backgrounds often have smaller file sizes, leading to faster load times and a better user experience on your website.

How to Remove Background from Image: A Step-by-Step Guide

One of the easiest ways to remove backgrounds from your product photos is through a web-based AI image background remover you will find via the link. With this tool, you can smoothly cut out any object in just a few clicks, save your picture with a transparent backdrop, or apply one of the 50+ included backgrounds — all of that completely free of charge. Below you’ll find a brief tutorial on how to do it using this tool:

Step 1. Upload Your Picture

Once you’ve opened the AI background remover, click the Upload Image button and select the product photo you wish to edit. You can load pictures in JPEG and PNG formats.

Step 2. AI Background Removal

Once your photo is uploaded, the AI tool will automatically detect the product and remove the backdrop. This process usually takes just a few seconds.

Step 3. Review and Download

After the AI finishes processing your image, you will see a preview result. Press the Save Photo button to download the picture with a transparent backdrop to your device. 

Alternative Programs to Use for Removing Backgrounds

Want to explore all the available program options? Here are a few good image background removers:

1. Adobe Photoshop

Want to use the gold standard of image editing and don’t mind the challenges of mastering the program? Photoshop is for you. This photo background remover offers unparalleled control over backdrop elimination with tools like the Magic Wand, Quick Selection, Lasso, Refine Edge, and advanced masking techniques. Its layer-based approach ensures precise editing, making it ideal for complex backgrounds or detailed product shots. However, subscribing to Creative Cloud is expensive if used infrequently.

2. GIMP

If you are looking for a background remover free of charge but with similar functionality to Photoshop, check out GIMP. This open-source image editor provides excellent capabilities for background removal. Its selection tools, including the intelligent Fuzzy Select and Foreground Select tools, cater to varying degrees of complexity in image backgrounds. With a supportive community and frequent updates, GIMP remains a strong choice for budget-conscious users.

3. Clipping Magic

Need a specialized tool that focuses solely on background removal? Look no further than Clipping Magic. Designed with simplicity in mind, it automates much of the process while still allowing for manual adjustments for precision. With an intuitive interface and AI-driven algorithms, it caters to users who are seeking efficiency without sacrificing quality. Its functionality is limited compared to more comprehensive editing software, though.

4. Fotor

Last but not least is Fotor. While primarily known for its photo editing and enhancement tools, this program also includes background removal features. It blends user-friendly design with powerful AI capabilities, making it accessible to both novice and seasoned editors who want an easy, quick solution.

Conclusion

Removing backgrounds from photos is not just a technical step but a strategic choice to enhance visual appeal and professionalism. Now, you can choose between a free online tool or one of the desktop alternatives, depending on your skill level, need for additional editing capabilities, manual selection, or faster processes. Start enhancing product photos for an online store or refining visuals for marketing campaigns to achieve professional results efficiently and effectively.

Apple is preparing for a major upgrade to the iPhone 16, reportedly increasing its order of chips from TMSC to some 90 to 100 million units. The company is clearly betting heavily that consumers are eager to try its new Apple Intelligence features that were demoed at WWDC 2024.

According to AppleInsider, Wedbush agrees with Apple, saying the iPhone 16 cycle will likely be “monumental” and “a massive upgrade cycle.”

In our own coverage of Apple’s AI announcements, we said WWDC was a case of Apple doing what it does best: provide solid, practical examples of how consumers can use AI in their everyday lives. This is something few, if any, of the leading AI firms have done.

Wedbush agrees with that assessment, saying Apple has effectively positioned itself as the “gatekeepers of the consumer AI Revolution,” (via Investing.com) something no other company has managed to achieve.

It should be no surprise that Apple is quickly being viewed that way, given the company’s long track record of democratizing technologies and spurring widespread adoption. While other companies invented the personal computer, the laptop, the portable music player, the smartphone, and the tablet, Apple has always had a penchant for elevating such products and designs in a way that competitors fail to do. The company also excels at making technologies that seem ambiguous or unattainable commonplace.

If the company is able to apply that approach to AI, in combination with its large user base, it could do more to drive AI adoption than most other companies combined.

Apple unveiled its Apple Intelligence (A.I.) at WWDC 2024, demonstrating a number of practical ways that A.I. will help streamline actions and workflows on the company’s devices. One of the headline features was Siri, with the virtual assistant receiving a supercharged upgrade, thanks to A.I. In fact, many see Siri finally achieving its full potential and living up to its promise as a result of the features Apple demoed.

Unfortunately, according to Bloomberg’s Mark Gurman, the new A.I. Siri won’t debut until at least iOS 18.4, which won’t make an appearance until next year:

Apple’s big Siri upgrade should arrive next spring. Siri’s new capabilities are bound to be a highlight of the Apple Intelligence rollout. For the first time, the digital assistant will have precise control over actions inside of Apple’s apps. That means you can ask Siri to, say, edit a photo and then ship it off to a friend. It also will have the ability to understand what you’re looking at on your display, helping Siri determine what you want to do based on the context. But neither of those upgrades will be ready when Apple Intelligence launches this fall, as I’ve previously reported.

Instead, I’m told, Siri features are likely to go into beta testing for developers in January and then debut publicly around the springtime — part of an iOS 18.4 upgrade that’s already in the works. Other Siri features, such as a new design and ChatGPT integration, will be coming later this year.

As we pointed out in our coverage of WWDC, Apple provided one of the most compelling arguments of any of the Big Tech companies about why people should care about artificial intelligence. The company demonstrated real-world examples of how the technology can be used to speed up everyday tasks. Apple is so confident in the usefulness of its A.I. features that the company is reportedly planning to offer a paid plan with more advanced features.

As a result of its A.I. features, Apple is expecting the iPhone 16 to be a major seller, with the company recently increasing its order of TSMC-supplied chips to between 90 and 100 million.

Companies large and small are investing billions in generative AI, with the financial firm saying those investments will top $1 trillion in the coming years. Despite the heavy cost, however, Goldman Sachs is warning in a report (via the Internet Archive)that “the technology isn’t designed to solve the complex problems that would justify the costs, which may not decline as many expect.”

Much of the issue stems from the high cost and the limited potential for AI to be capable enough to be cost-effective any time in the near future, as Goldman Sachs points out:

We first speak with Daron Acemoglu, Institute Professor at MIT, who’s skeptical. He estimates that only a quarter of AI- exposed tasks will be cost-effective to automate within the next 10 years, implying that AI will impact less than 5% of all tasks. And he doesn’t take much comfort from history that shows technologies improving and becoming less costly over time, arguing that AI model advances likely won’t occur nearly as quickly—or be nearly as impressive—as many believe. He also questions whether AI adoption will create new tasks and products, saying these impacts are “not a law of nature.” So, he forecasts AI will increase US productivity by only 0.5% and GDP growth by only 0.9% cumulatively over the next decade.

GS Head of Global Equity Research Jim Covello was even more pessimistic, contrasting AI’s high cost to other industry-disrupting technologies that started out far more cost-effective:

Many people attempt to compare AI today to the early days of the internet. But even in its infancy, the internet was a low-cost technology solution that enabled e-commerce to replace costly incumbent solutions. Amazon could sell books at a lower cost than Barnes & Noble because it didn’t have to maintain costly brick-and-mortar locations. Fast forward three decades, and Web 2.0 is still providing cheaper solutions that are disrupting more expensive solutions, such as Uber displacing limousine services. While the question of whether AI technology will ever deliver on the promise many people are excited about today is certainly debatable, the less debatable point is that AI technology is exceptionally expensive, and to justify those costs, the technology must be able to solve complex problems, which it isn’t designed to do.

Covello goes on to tell Goldman Sachs that he’s skeptical that AI can achieve the transformative effect that the internet, cell phones, and laptops have achieved.

More broadly, people generally substantially overestimate what the technology is capable of today. In our experience, even basic summarization tasks often yield illegible and nonsensical results. This is not a matter of just some tweaks being required here and there; despite its expensive price tag, the technology is nowhere near where it needs to be in order to be useful for even such basic tasks. And I struggle to believe that the technology will ever achieve the cognitive reasoning required to substantially augment or replace human interactions. Humans add the most value to complex tasks by identifying and understanding outliers and nuance in a way that it is difficult to imagine a model trained on historical data would ever be able to do.

Others—such as GS senior global economist Joseph Briggs and internet analyst Eric Sheridan—were slightly more optimistic. Briggs sees AI automating as much as 25% of work in the next decade, and raising US productivity by 9% and GDP by 6.1%.

Ultimately, it may be the industries that support AI to be the ones that most benefit from it before a potential bust, according to Goldman Sachs:

Although Covello believes AI’s fundamental story is unlikely to hold up, he cautions that the AI bubble could take a long time to burst, with the “picks and shovels” AI infrastructure providers continuing to benefit in the meantime. GS senior US equity strategist Ryan Hammond also sees more room for the AI theme to run and expects AI beneficiaries to broaden out beyond just Nvidia, and particularly to what looks set to be the next big winner: Utilities.

That said, looking at the bigger picture, GS senior multi-asset strategist Christian Mueller-Glissmann finds that only the most favorable AI scenario, in which AI significantly boosts trend growth and corporate profitability without raising inflation, would result in above-average long-term S&P 500 returns, making AI’s ability to deliver on its oft-touted potential even more crucial.

Goldman Sach’s full report is well worth a read and illustrates in detail the challenges facing the AI industry. As the report highlights, companies will need to demonstrate that AI can deliver on its promise if the vast investments are to be justified. Otherwise utilities and chip companies may be the only industries to see a return that’s worth it.

Nvidia is not only the leading GPU maker but also the company that virtually the entire tech industry relies on to power their AI models. The company’s position has helped it become the world’s most valuable company, surpassing both Apple and Microsoft.

According to Reuters, however, that success has come with newfound regulatory scrutiny, with France preparing to file antitrust charges. The report follows the country’s competition authority raid on Nvidia’s offices last September.

The outlet reports that the French watchdog issued a report last week that cited a number of concerns about the AI industry in general, including Nvidia’s CUDA being dominant, as well as Nvidia’s investments AI cloud service providers.

While the EU Commission has launched a preliminary review of Nvidia, it seems the Commission is likely waiting for the French case to play out before expanding its investigation.

Broadening Horizons: Sectors Embracing AI

The conversation with Thomas Siebel revealed AI’s expansive reach, with various sectors eagerly adopting these technologies to revolutionize their operations. “The Public sector is huge,” Siebel emphasized, pointing to the significant demand from state and local governments. We see substantial opportunities in manufacturing, aerospace, telecommunications, and consumer packaged goods. It’s really across the board.”

Siebel provided an illustrative example from the construction materials sector in Europe, where a significant transaction is underway. “This is all about digital transformation and optimizing processes,” he said. “We are focusing on energy efficiency and decarbonization, which are critical components of our clients’ sustainability goals.” The European deal is just one among many, demonstrating the widespread application of AI in enhancing operational efficiency and sustainability.

AI Helping To Streamline Production Lines

The manufacturing sector has particularly shown keen interest in AI-driven solutions. “In manufacturing, AI is helping to streamline production lines, reduce waste, and improve overall efficiency,” Siebel noted. “We are seeing companies leverage AI to predict equipment failures before they happen, saving millions in downtime and maintenance costs.” This predictive capability is transforming how industries manage their operations, leading to significant cost savings and increased productivity.

In the aerospace sector, AI is being used to enhance safety and efficiency. “Aerospace companies are using AI to optimize flight paths, improve fuel efficiency, and conduct predictive maintenance on aircraft,” Siebel explained. “The ability to anticipate and address issues before they occur is a game-changer for the industry.” This proactive approach enhances safety and reduces operational costs and downtime.

Telecommunications is another sector experiencing the transformative effects of AI. “Telecom companies are using AI to manage their networks more efficiently, improve customer service, and develop new revenue streams,” Siebel said. “By leveraging AI, they can offer personalized services and quickly resolve network issues, leading to higher customer satisfaction.” This shift towards AI-driven operations is helping telecom companies stay competitive in a rapidly evolving market.

AI Used To Enhance Customer Engagement

Consumer packaged goods companies also embrace AI to optimize their supply chains and enhance customer engagement. “In consumer packaged goods, AI is helping companies better understand consumer preferences, manage inventory, and streamline their supply chains,” Siebel noted. “By analyzing vast amounts of data, these companies can make more informed decisions and respond more quickly to market changes.” This data-driven approach is enabling companies to stay agile and responsive in a highly competitive landscape.

Siebel’s insights underscore the transformative potential of AI across various sectors. As industries continue to adopt AI-driven solutions, the benefits in terms of efficiency, cost savings, and sustainability are becoming increasingly evident. “AI is not just a tool for the future; it’s a critical component of today’s business strategy,” Siebel concluded. “We are only scratching the surface of what’s possible with AI, and the opportunities are immense.”

Federal Government: A Major Growth Driver

Thomas Siebel highlighted the federal government as a significant source of growth for C3.AI, noting a remarkable 100% increase in federal government revenue last quarter. “The federal government is undergoing a massive digital transformation,” Siebel explained. “Defense and intelligence sectors are leading the charge, leveraging AI for everything from aircraft maintenance and asset management to logistics and supply chain optimization.”

Siebel emphasized AI’s strategic importance in national security. “AI is at the heart of modern defense strategies,” he said. The intelligence community is transforming to take advantage of what we call the ‘kill chain’ of the future—hypersonic swarms, sub-surface vehicles, and cyber warfare.” This transformation involves integrating AI to enhance the efficiency and effectiveness of military operations, making it a critical component of national defense.

AI Helping To Safeguard National Security

The integration of AI into defense operations is not just about enhancing current capabilities but also about preparing for future challenges. “We are seeing significant investments in AI to predict and mitigate threats before they materialize,” Siebel noted. “This includes everything from analyzing signals from satellites to improving cybersecurity measures.” The proactive use of AI in these areas is helping to safeguard national security and ensure the country remains ahead of emerging threats.

Beyond defense, the federal government also uses AI to optimize various administrative functions. “AI is being utilized to improve the efficiency of government operations,” Siebel said. “This includes everything from streamlining administrative processes to enhancing public service delivery.” By leveraging AI, government agencies can better manage resources, reduce costs, and provide more effective services to the public.

Government’s Scale Illustrates AI’s Transformative Power

Siebel pointed out that the public sector’s adoption of AI sets a precedent for other industries. “The federal government’s commitment to AI showcases its potential and encourages other sectors to follow suit,” he explained. “As public sector entities demonstrate the benefits of AI, it creates a ripple effect, prompting private companies to adopt similar technologies.” This trend is accelerating the overall adoption of AI across various sectors, driving further innovation and growth.

The federal government’s role as a major growth driver for C3.AI underscores AI’s broader potential to transform large organizations. “The scale at which the federal government operates provides a unique opportunity to showcase AI’s capabilities,” Siebel concluded. The lessons learned and successes achieved in the public sector can serve as a blueprint for other industries, illustrating AI’s transformative power.”

Enterprise Software and AI: A Synergistic Relationship

The enterprise software market, a $600 billion global industry, is undergoing a significant transformation as it begins to integrate artificial intelligence (AI) into its offerings. Thomas Siebel, CEO of C3.AI, explained how AI revolutionizes traditional enterprise software, creating a synergistic relationship that enhances capabilities rather than replaces existing systems. “The enterprise software stacks were built in the 20th century and, while sophisticated, do not incorporate AI,” Siebel noted. “Our approach is not to replace these systems but to augment them with predictive capabilities that drive greater efficiency and innovation.”

AI’s role in enterprise software is multifaceted, providing predictive analytics that enables businesses to address issues before they escalate preemptively. “We allow companies to predict customer churn, machinery breakdowns, and supply chain disruptions,” Siebel said. “For instance, if we can predict which customers are likely to leave, businesses can take proactive steps to retain them.” This predictive power transforms how companies manage their operations, shifting from reactive to proactive strategies that save time and resources.

AI Driving Digital Transformation

One of the key advantages of integrating AI with enterprise software is the ability to handle large and complex infrastructures. “AI can predict failures in large-scale systems like the power grid or oil and gas infrastructure,” Siebel explained. “This capability is crucial for maintaining continuous operations and preventing costly downtime.” By leveraging AI, companies can enhance the reliability and resilience of their critical infrastructure, ensuring smoother and more efficient operations.

The shift towards AI-enhanced enterprise software also aligns with broader trends in digital transformation and data utilization. “Data is at the core of AI, and the ability to harness this data effectively is what sets successful companies apart,” Siebel emphasized. “We are seeing organizations across all sectors investing heavily in AI to unlock new insights and drive performance improvements.” This investment is about keeping pace with technological advancements and gaining a competitive edge in an increasingly data-driven world.

Despite the clear benefits, the transition to AI-integrated enterprise software is challenging. Siebel acknowledged that changing the pricing model from subscription to pay-as-you-go has impacted some metrics but emphasized the long-term advantages. “We changed our pricing model to align better with our customers’ needs and to drive sustainable revenue growth,” he said. “While this has caused a dip in certain metrics, it positions us for stronger, more consistent growth in the future.”

As businesses navigate digital transformation’s complexities, integrating AI into enterprise software represents a significant leap forward. “AI is not just an add-on; it’s a fundamental shift in how we approach business operations,” Siebel concluded. “The synergy between enterprise software and AI is creating unprecedented opportunities for innovation, efficiency, and growth. As we continue to develop and deploy these technologies, we are laying the groundwork for a new era of intelligent enterprise solutions.”

Adapting to New Pricing Models

As C3.AI continues to evolve, a significant shift has transitioned from a subscription-based pricing model to a pay-as-you-go structure. This change, while impactful, is designed to better align with customer needs and drive sustainable revenue growth. Thomas Siebel, CEO of C3.AI, explained the rationale behind this strategic move, emphasizing its benefits despite some initial challenges. “We shifted our pricing model to a pay-as-you-go structure to provide greater flexibility and scalability for our customers,” Siebel stated. “This approach allows them to pay for what they use, making it more cost-effective and accessible.”

The new pricing model has had a noticeable impact on certain financial metrics, notably the remaining performance obligation (RPO), which saw a year-over-year decline of 36%. However, Siebel remains confident that this shift is beneficial in the long run. “While the RPO metric reflects a decrease, it’s important to understand that this is part of our strategic adaptation to market demands,” he explained. “Our focus is on driving revenue growth through increased usage and customer satisfaction, which we believe will lead to stronger financial performance over time.”

Customers Embracing Pay-As-You-Go-Model

Customers have responded positively to the increased flexibility provided by the pay-as-you-go model. This adaptability is particularly valuable for organizations navigating uncertain economic conditions and fluctuating demand. “Our customers appreciate the ability to scale their usage up or down based on their immediate needs without being locked into long-term contracts,” Siebel noted. “This flexibility is crucial in today’s fast-paced business environment, where agility and responsiveness are key competitive advantages.”

The pay-as-you-go model also aligns with the broader trend toward consumption-based pricing in the technology sector. Companies can better manage their budgets and allocate resources more efficiently by only paying for what they use. “This model encourages efficient use of resources and ensures that customers get maximum value from their investment,” Siebel said. “It also allows us to build stronger, more dynamic relationships with our clients, as their success directly translates into our success.”

Looking ahead, Siebel sees the new pricing model as a cornerstone of C3.AI’s growth strategy. “We believe that this approach will enhance our competitive position and drive long-term growth and profitability,” he asserted. “As more organizations recognize the benefits of AI and digital transformation, the demand for flexible, scalable solutions will continue to rise. Our pay-as-you-go model positions us well to capitalize on this trend and deliver exceptional value to our customers.”

The transition to a pay-as-you-go model is more than just a pricing change; it’s a strategic pivot that reflects C3.AI’s commitment to innovation and customer-centricity. “We’re not just adapting to the market; we’re shaping it,” Siebel concluded. “By offering flexible, scalable solutions, we’re enabling our customers to harness the full potential of AI and drive their digital transformation initiatives forward. This is the future of enterprise technology, and we’re excited to lead the way.”

Navigating a Transformative Landscape

As C3.AI continues to navigate the dynamic landscape of artificial intelligence and enterprise software, its strategic initiatives underscore its commitment to innovation and adaptability. The transition to a pay-as-you-go pricing model, the expansion into diverse sectors, and the significant growth within the federal government sector all highlight C3.AI’s agility in responding to market demands and technological advancements.

Thomas Siebel, CEO of C3.AI, encapsulates the company’s forward-looking vision: “We are at the forefront of a technological revolution that is reshaping industries and redefining the possibilities of enterprise AI. Our focus remains on delivering scalable, flexible solutions that empower our customers to achieve their digital transformation goals.” This vision is supported by the company’s robust pipeline of new deals and its strategic partnerships across various sectors, which position C3.AI as a leader in the AI-driven digital transformation space.

Innovation at the Heart of Everything We Do

The company’s success is also driven by its ability to innovate continuously. “Innovation is at the heart of everything we do,” Siebel emphasized. “From enhancing our AI models to optimizing our pricing strategies, we are committed to pushing the boundaries of what is possible and delivering unparalleled value to our customers.” This commitment to innovation is evident in the company’s ability to attract and retain a diverse range of clients, from state and local governments to manufacturing and telecommunications firms.

Moreover, C3.AI’s growth in the federal government sector underscores its role in advancing critical national interests. “Our work with the federal government, particularly in defense and intelligence, highlights the strategic importance of AI in modern warfare and national security,” Siebel noted. “We are proud to support these initiatives and contribute to the development of the ‘kill chain’ of the future, encompassing hypersonic swarms, sub-surface vehicles, and cyberwarfare capabilities.”

As C3.AI continues to expand its footprint, the company remains focused on its core mission of driving digital transformation and optimizing client processes. “We are dedicated to helping our customers achieve greater efficiency, reduce costs, and enhance their overall performance,” Siebel said. “By leveraging the power of AI, we are enabling organizations to make smarter, data-driven decisions and stay ahead in an increasingly competitive landscape.”

Just Scratching the Surface of What AI Can Achieve

Looking ahead, Siebel is optimistic about the future of C3.AI and the broader AI industry. “We are just scratching the surface of what AI can achieve,” he asserted. “As technology continues to evolve, we will see even greater integration of AI into all aspects of business and society. C3.AI is well-positioned to lead this transformation and deliver cutting-edge solutions that drive real-world impact.”

In conclusion, C3.AI’s journey is a testament to its resilience, innovation, and strategic vision. By navigating the complexities of the AI landscape and adapting to changing market conditions, the company is poised for continued growth and success. As Siebel aptly stated, “The future of AI is bright, and we are excited to be at the forefront of this transformative journey, driving innovation and delivering value for our customers and stakeholders.”

A user on the OpenAI forums posted an email from the company regarding API usage. The email reads as follows:

*Hello,

Our data shows that your organization has API traffic from a region that OpenAI does not currently support. You can find the supported countries and territories here. We will be taking additional measures to block API traffic from regions that are not on our supported countries and territories list starting on July 9. To continue using OpenAI’s services, you will need to access the service in a supported region.

If you have any questions please visit our help center.

Thank you,

The OpenAI Team*

The user goes on to say that they don’t know why there is API access from unsupported territories, but some users suggest it could an application deployed via Cloudflare Worker that is being run on the edge.

Either way, OpenAI’s email should serve as a warning to organizations to be mindful where their apps are run from.

Below is the complete list of supported countries and territories:

• Albania
• Algeria
• Afghanistan
• Andorra
• Angola
• Antigua and Barbuda
• Argentina
• Armenia
• Australia
• Austria
• Azerbaijan
• Bahamas
• Bahrain
• Bangladesh
• Barbados
• Belgium
• Belize
• Benin
• Bhutan
• Bolivia
• Bosnia and Herzegovina
• Botswana
• Brazil
• Brunei
• Bulgaria
• Burkina Faso
• Burundi
• Cabo Verde
• Cambodia
• Cameroon
• Canada
• Central African Republic
• Chad
• Chile
• Colombia
• Comoros
• Congo (Brazzaville)
• Congo (DRC)
• Costa Rica
• Côte d’Ivoire
• Croatia
• Cyprus
• Czechia (Czech Republic)
• Denmark
• Djibouti
• Dominica
• Dominican Republic
• Ecuador
• Egypt
• El Salvador
• Equatorial Guinea
• Eritrea
• Estonia
• Eswatini (Swaziland)
• Ethiopia
• Fiji
• Finland
• France
• Gabon
• Gambia
• Georgia
• Germany
• Ghana
• Greece
• Grenada
• Guatemala
• Guinea
• Guinea-Bissau
• Guyana
• Haiti
• Holy See (Vatican City)
• Honduras
• Hungary
• Iceland
• India
• Indonesia
• Iraq
• Ireland
• Israel
• Italy
• Jamaica
• Japan
• Jordan
• Kazakhstan
• Kenya
• Kiribati
• Kuwait
• Kyrgyzstan
• Laos
• Latvia
• Lebanon
• Lesotho
• Liberia
• Libya
• Liechtenstein
• Lithuania
• Luxembourg
• Madagascar
• Malawi
• Malaysia
• Maldives
• Mali
• Malta
• Marshall Islands
• Mauritania
• Mauritius
• Mexico
• Micronesia
• Moldova
• Monaco
• Mongolia
• Montenegro
• Morocco
• Mozambique
• Myanmar
• Namibia
• Nauru
• Nepal
• Netherlands
• New Zealand
• Nicaragua
• Niger
• Nigeria
• North Macedonia
• Norway
• Oman
• Pakistan
• Palau
• Palestine
• Panama
• Papua New Guinea
• Paraguay
• Peru
• Philippines
• Poland
• Portugal
• Qatar
• Romania
• Rwanda
• Saint Kitts and Nevis
• Saint Lucia
• Saint Vincent and the Grenadines
• Samoa
• San Marino
• Sao Tome and Principe
• Saudi Arabia
• Senegal
• Serbia
• Seychelles
• Sierra Leone
• Singapore
• Slovakia
• Slovenia
• Solomon Islands
• Somalia
• South Africa
• South Korea
• South Sudan
• Spain
• Sri Lanka
• Suriname
• Sweden
• Switzerland
• Sudan
• Taiwan
• Tajikistan
• Tanzania
• Thailand
• Timor-Leste (East Timor)
• Togo
• Tonga
• Trinidad and Tobago
• Tunisia
• Turkey
• Turkmenistan
• Tuvalu
• Uganda
• Ukraine (with certain exceptions)
• United Arab Emirates
• United Kingdom
• United States of America
• Uruguay
• Uzbekistan
• Vanuatu
• Vietnam
• Yemen
• Zambia
• Zimbabwe