Can AI even be open source? It’s complicated zf L/Getty Images
Without open source, there is no artificial intelligence (AI). Period. End of statement.
It’s not just that AI’s early roots spring from the 1960s’ open language Lisp; the headline AI generative models, such as ChatGPT, Llama 2, and DALL-E, are built on solid, open-source foundations. However, those models and programs themselves are not open source.
Also: AI scientist: ‘We need to think outside the large language model box’
Oh, I know that when Meta CEO Mark Zuckerberg unveiled Llama 3.1 in a Threads post, he said, “Open-source AI is the path forward,” and that Meta is “taking the next steps towards open-source AI becoming the industry standard.”
At a SIGGRAPH keynote discussion with Nvidea CEO Jensen Huang, Zuckerberg admitted:
We’re not pursuing [open source] out of altruism, though I believe it will benefit the ecosystem. We’re doing it because we think it will enhance our offerings by creating a strong ecosystem. … this might sound selfish, but after building this company for a while, one of my goals for the next 10 or 15 years is to ensure we can build the fundamental technology for our social experiences.
Zuckerberg is sincere about open source. As we’ve seen repeatedly, open source is the way to unite technologies. For example, we use a unified Linux now instead of multiple, incompatible versions of Unix because Linus Torvalds open-sourced Linux under GPLv2.
Also: A new White House report embraces open-source AI
But I’ve also read Meta’s Llama 2 license and the Llama Acceptable Use Policy. It’s not open source. It’s not even close.
Zuck’s not alone, though, in playing fast and loose with open source. From the name, you’d think OpenAI is open source. It was indeed open back when GPT-1 and GPT-2 were state-of-the-art. That was a long time — and billions in revenue — ago. Starting with GPL-3, OpenAI closed its doors.
As Mark Dingemanse, a language scientist at Radboud University in Nijmegen, Netherlands said in a Nature article, “Some big firms are reaping the benefits of claiming to have open-source models while trying “to get away with disclosing as little as possible.”
Indeed, Dingemanse and his colleague Andreas Liesenfeld found only one AI chatbot that could truly be described as open: The Hugging Face-hosted Large-Language Model (LLM) BigScience/BloomZ.
Other LLMs that qualify are Falcon, FastChat-T5, and OpenLLaMA. But most LLMs contain proprietary, copyrighted, or simply unknown information their owners won’t tell you about. As the Electronic Frontier Foundation (EFF) observed, “Garbage In, Gospel Out.”
Now, much of the innovative software driving AI is open source. TensorFlow is a versatile learning framework that supports multiple programming languages and is used for machine learning. PyTorch is popular for its dynamic computational graphs and ease of use in deep learning applications that quickly come to mind.
Also: How open source attracts some of the world’s top innovators
The LLMs and programs built on them are another story. All the most popular AI chatbots and programs are proprietary.
So, why are companies claiming their projects are open source? By “open-washing” their efforts, businesses hope to gild their programs with open source’s positive connotations of transparency, collaboration, and innovation. They also hope to con developers into helping advance their own projects. It’s all about marketing.
Clearly, we need to devise an open-source definition that fits AI programs to stop these faux-source efforts in their tracks. Unfortunately, that’s easier said than done.
While people constantly fuss over the finer details of what’s open-source code and what isn’t, the Open Source Initiative (OSI) has nailed down the definition, the Open Source Definition (OSD), for almost twenty years. The convergence of open source and AI is much more complicated.
In fact, Joseph Jacks, founder of the Venture Capitalist (VC) business FOSS Capital, argued there is “no such thing as open-source AI” since “open source was invented explicitly for software source code.”
It’s true. In addition, open-source’s legal foundation is copyright law. As Jacks observed, “Neural Net Weights (NNWs) [which are essential in AI] are not software source code — they are unreadable by humans, nor are they debuggable.”
As Stefano Maffulli, OSI executive director, has told me, software and data are mixed in AI, and existing open-source licenses are breaking down. Specifically, trouble emerges when all that data and code are merged in AI/ML artifacts — such as datasets, models, and weights. “Therefore, we need to make a new definition for open-source AI,” said Mafulli.
Also: Switzerland’s federal government requires releasing its software as open source
However, getting there hasn’t been easy. The main point of contention is the extent of openness required, particularly regarding training data. While some argue that releasing pre-trained models without the training data is sufficient, others argue that true open-source AI should also include access to the training data.
As julia ferraioli (Stet: she spells her name in all lower case), Amazon Web Services (AWS) Open Source AI/ML Strategist, observed in a blog post, with the current OSI open-source AI definition 0.08 draft, “the only aspects of the data that a system desiring to be labeled as ‘open source AI’ would need to publish are: training methodologies and techniques; training data scope and characteristics; training data provenance (including how data was obtained and selected), training data labeling procedures, and training data cleaning methodology.”
None of that, ferraioli continued, “gives the prospective adopter of the AI system insight into the data that was used to train the system.” Without this data, can an AI be open? Ferraioli argues it can’t.
She’s not the only one who holds that position. She quotes her colleague, AWS Principal Open Source Technical Strategist Tom Callaway, who wrote, “Without requiring the data be open, it is not possible for anyone without the data to fully study or modify the LLM, or distribute all of its source code. You can only use it, tune/tweak it a bit, but you can’t dive deep into it to understand why it does what it does.”
Also: More than money, open-source pros want these 2 things from their next jobs
He has a good point. At its heart, open source is all about understanding the code. In AI’s case, that means the data as well. As Maffulli said at the recent United Nations OSPOs for Good Conference, “While there’s broad agreement on the overarching principles, it’s becoming obvious that the devil is in the details.” You can say that again.
At the same conference, Sasha Luccioni, Hugging Face’s AI and climate lead, argued, “You can’t really expect all companies to be 100% open source as the open source license defines it. You can’t expect companies just to give up everything that they’re making money off of and do so in a way they’re comfortable with.”
Still, Luccioni believes “a responsible AI license can exist” — one that is open source friendly — where you can define your terms of open source. By tweaking the language a little bit, you can move forward in a way that companies, governments, and academia are all comfortable with instead of saying this project or license is not open source.
Also: Why don’t more people use desktop Linux? I have a theory you might not like
Open-source advocates disagreed. I suspect the arguments will continue for years to come.
The OSI, with the help of 70 others, consisting of researchers, lawyers, policymakers, activists, and representatives from big tech companies like Meta, Google, and Amazon and groups such as the Linux Foundation and the Alfred P. Sloan Foundation, is wrestling to come up with a workable definition. The goal is to present a stable version of the Open Source AI Definition at the next All Things Open conference in Raleigh, North Carolina, from October 27th to the 29th.
I’ll be there. So strap in, folks. The combination of open-source principles and AI development is driving significant advancements. It’s also enabling faster innovation, promoting collaboration, and democratizing access to powerful AI tools. But, its evolution promises to be a long, difficult process.
You Won’t Need to Pay for Apple Intelligence Anytime Soon
Despite several analyst reports that Apple will eventually charge for access to Apple Intelligence features, it’s unlikely it plans to do so anytime soon.
While many, including Mark Gurman, believe that Apple’s focus on growing its services business makes a paid Apple Intelligence tier inevitable, the Bloomberg analyst is also convinced this won’t be coming in the near future — and that it’s unlikely to encompass any of the Apple Intelligence features that are slated to arrive in iOS 18 over the next year.
In late June, Gurman suggested an “Apple Intelligence+” tier could eventually arrive with a monthly fee, but it would most likely consist of extra new features rather than putting things like Siri personal context, Image Playground, and Genmoji behind a paywall.
More analysts chimed in last week to suggest a $20 monthly price tag, although it seems like they’re pulling that number out of thin air based on what they feel the market will bear. For example, OpenAI charges $20 per month for its ChatGPT Plus subscription, but that’s not a fair comparison to what Apple is likely to do since OpenAI’s paid plans are about providing higher usage limits more than additional features.
However, amidst all this speculation, Gurman has offered an important point of clarification. While he maintains in his latest Power On newsletter that a paid Apple Intelligence tier will eventually arrive, he also emphasizes that it will be years before Apple is ready to go there.
That’s because Gurman doesn’t expect Apple Intelligence to be a mature product that people will be willing to pay for before 2027 — and he calls that a “best-case scenario.”
Apple isn’t foolish enough to try to charge high fees for something that’s not ready for prime time. Say what you will about Apple TV+ when it first launched in 2019, but even though it had a limited catalog of content, and what was there may not have been everyone’s cup of tea, it still had some big-name talent on board. It also launched at a much lower price than any other streaming service — a price it later admitted was deliberately set low to reflect the smaller amount of content available at launch.
Apple Intelligence is arguably launching early in response to the AI hype, but it will be well into 2025 before it offers everything that Apple showed us during its Worldwide Developers Conference (WWDC).
The second iOS 18.1 beta came out earlier this week with preliminary Apple Intelligence features, which still excludes the really fun stuff like Genmoji and Image Playground. Those might be ready by the time iOS 18.1 gets released in October, but ChatGPT integration probably won’t show up until iOS 18.2, and we already know that the more powerful Siri and personal context features aren’t likely to appear until iOS 18.4.
Then there’s the wrinkle that Apple Intelligence is only available in the US English and is restricted in the European Union and China due to regulatory issues. Apple has promised to add more languages over the next year, but there’s no word on when those will show up, and while it’s also working on the regulatory hurdles, that could take even longer.
As it stands now, Apple Intelligence may not be fully baked until iOS 19 arrives next year, and even then, it’s hard to imagine Apple being ready to add even more features that will be worth charging for.
Lastly, it’s important to remember that everything that’s been said about Apple charging for Apple Intelligence is educated speculation, at best. Apple has not even hinted that it will try to monetize any of these features directly from end users. It’s likely getting a cut from ChatGPT subscriptions made through Apple Intelligence, but that’s a typical arrangement for every in-app subscription.
That’s in contrast to Emergency SOS via satellite. When Apple launched that in 2022 with the iPhone 14 lineup, it made it clear that it could eventually start charging for satellite access, promising iPhone 14 owners only two years of free access. It has yet to say what will happen when that time is up, but it’s already extended that into late 2025, matching the two years that new iPhone 15 buyers would have received at launch. Only Apple knows when or if it will charge for satellite access, but it’s left the door open to do so. That’s not the case with Apple Intelligence.
While Apple is undoubtedly looking at ways it can grow its services business, it’s not trying to turn everything into a subscription service, and rumors of a paid Apple Intelligence+ tier could end up carrying as much weight as earlier rumors of things like Apple Mail+ and Apple Health+.
[The information provided in this article has NOT been confirmed by Apple and may be speculation. Provided details may not be factual. Take all rumors, tech or otherwise, with a grain of salt.]
Can AI even be open source? It’s complicated zf L/Getty Images
Without open source, there is no artificial intelligence (AI). Period. End of statement.
It’s not just that AI’s early roots spring from the 1960s’ open language Lisp; the headline AI generative models, such as ChatGPT, Llama 2, and DALL-E, are built on solid, open-source foundations. However, those models and programs themselves are not open source.
Also: AI scientist: ‘We need to think outside the large language model box’
Oh, I know that when Meta CEO Mark Zuckerberg unveiled Llama 3.1 in a Threads post, he said, “Open-source AI is the path forward,” and that Meta is “taking the next steps towards open-source AI becoming the industry standard.”
At a SIGGRAPH keynote discussion with Nvidea CEO Jensen Huang, Zuckerberg admitted:
We’re not pursuing [open source] out of altruism, though I believe it will benefit the ecosystem. We’re doing it because we think it will enhance our offerings by creating a strong ecosystem. … this might sound selfish, but after building this company for a while, one of my goals for the next 10 or 15 years is to ensure we can build the fundamental technology for our social experiences.
Zuckerberg is sincere about open source. As we’ve seen repeatedly, open source is the way to unite technologies. For example, we use a unified Linux now instead of multiple, incompatible versions of Unix because Linus Torvalds open-sourced Linux under GPLv2.
Also: A new White House report embraces open-source AI
But I’ve also read Meta’s Llama 2 license and the Llama Acceptable Use Policy. It’s not open source. It’s not even close.
Zuck’s not alone, though, in playing fast and loose with open source. From the name, you’d think OpenAI is open source. It was indeed open back when GPT-1 and GPT-2 were state-of-the-art. That was a long time — and billions in revenue — ago. Starting with GPL-3, OpenAI closed its doors.
As Mark Dingemanse, a language scientist at Radboud University in Nijmegen, Netherlands said in a Nature article, “Some big firms are reaping the benefits of claiming to have open-source models while trying “to get away with disclosing as little as possible.”
Indeed, Dingemanse and his colleague Andreas Liesenfeld found only one AI chatbot that could truly be described as open: The Hugging Face-hosted Large-Language Model (LLM) BigScience/BloomZ.
Other LLMs that qualify are Falcon, FastChat-T5, and OpenLLaMA. But most LLMs contain proprietary, copyrighted, or simply unknown information their owners won’t tell you about. As the Electronic Frontier Foundation (EFF) observed, “Garbage In, Gospel Out.”
Now, much of the innovative software driving AI is open source. TensorFlow is a versatile learning framework that supports multiple programming languages and is used for machine learning. PyTorch is popular for its dynamic computational graphs and ease of use in deep learning applications that quickly come to mind.
Also: How open source attracts some of the world’s top innovators
The LLMs and programs built on them are another story. All the most popular AI chatbots and programs are proprietary.
So, why are companies claiming their projects are open source? By “open-washing” their efforts, businesses hope to gild their programs with open source’s positive connotations of transparency, collaboration, and innovation. They also hope to con developers into helping advance their own projects. It’s all about marketing.
Clearly, we need to devise an open-source definition that fits AI programs to stop these faux-source efforts in their tracks. Unfortunately, that’s easier said than done.
While people constantly fuss over the finer details of what’s open-source code and what isn’t, the Open Source Initiative (OSI) has nailed down the definition, the Open Source Definition (OSD), for almost twenty years. The convergence of open source and AI is much more complicated.
In fact, Joseph Jacks, founder of the Venture Capitalist (VC) business FOSS Capital, argued there is “no such thing as open-source AI” since “open source was invented explicitly for software source code.”
It’s true. In addition, open-source’s legal foundation is copyright law. As Jacks observed, “Neural Net Weights (NNWs) [which are essential in AI] are not software source code — they are unreadable by humans, nor are they debuggable.”
As Stefano Maffulli, OSI executive director, has told me, software and data are mixed in AI, and existing open-source licenses are breaking down. Specifically, trouble emerges when all that data and code are merged in AI/ML artifacts — such as datasets, models, and weights. “Therefore, we need to make a new definition for open-source AI,” said Mafulli.
Also: Switzerland’s federal government requires releasing its software as open source
However, getting there hasn’t been easy. The main point of contention is the extent of openness required, particularly regarding training data. While some argue that releasing pre-trained models without the training data is sufficient, others argue that true open-source AI should also include access to the training data.
As julia ferraioli (Stet: she spells her name in all lower case), Amazon Web Services (AWS) Open Source AI/ML Strategist, observed in a blog post, with the current OSI open-source AI definition 0.08 draft, “the only aspects of the data that a system desiring to be labeled as ‘open source AI’ would need to publish are: training methodologies and techniques; training data scope and characteristics; training data provenance (including how data was obtained and selected), training data labeling procedures, and training data cleaning methodology.”
None of that, ferraioli continued, “gives the prospective adopter of the AI system insight into the data that was used to train the system.” Without this data, can an AI be open? Ferraioli argues it can’t.
She’s not the only one who holds that position. She quotes her colleague, AWS Principal Open Source Technical Strategist Tom Callaway, who wrote, “Without requiring the data be open, it is not possible for anyone without the data to fully study or modify the LLM, or distribute all of its source code. You can only use it, tune/tweak it a bit, but you can’t dive deep into it to understand why it does what it does.”
Also: More than money, open-source pros want these 2 things from their next jobs
He has a good point. At its heart, open source is all about understanding the code. In AI’s case, that means the data as well. As Maffulli said at the recent United Nations OSPOs for Good Conference, “While there’s broad agreement on the overarching principles, it’s becoming obvious that the devil is in the details.” You can say that again.
At the same conference, Sasha Luccioni, Hugging Face’s AI and climate lead, argued, “You can’t really expect all companies to be 100% open source as the open source license defines it. You can’t expect companies just to give up everything that they’re making money off of and do so in a way they’re comfortable with.”
Still, Luccioni believes “a responsible AI license can exist” — one that is open source friendly — where you can define your terms of open source. By tweaking the language a little bit, you can move forward in a way that companies, governments, and academia are all comfortable with instead of saying this project or license is not open source.
Also: Why don’t more people use desktop Linux? I have a theory you might not like
Open-source advocates disagreed. I suspect the arguments will continue for years to come.
The OSI, with the help of 70 others, consisting of researchers, lawyers, policymakers, activists, and representatives from big tech companies like Meta, Google, and Amazon and groups such as the Linux Foundation and the Alfred P. Sloan Foundation, is wrestling to come up with a workable definition. The goal is to present a stable version of the Open Source AI Definition at the next All Things Open conference in Raleigh, North Carolina, from October 27th to the 29th.
I’ll be there. So strap in, folks. The combination of open-source principles and AI development is driving significant advancements. It’s also enabling faster innovation, promoting collaboration, and democratizing access to powerful AI tools. But, its evolution promises to be a long, difficult process.
Apple Intelligence EU: Potential Mac Release Amid DMA Rules
There is evidence that the EU may get Apple Intelligence after all — thanks to a tiny difference in the release notes for macOS Sequoia 15.1 and iOS 18.1. It was previously thought that the AI feature would not be available in the bloc on any Apple device due to the Digital Markets Act.
Apple Intelligence is a suite of generative AI capabilities to be integrated into the next generation of Apple devices running on iOS 18, iPadOS 18, and macOS Sequoia. Back in June, the Cupertino giant revealed that devices in the EU will not come with Apple Intelligence this year, via Bloomberg. This was due to “regulatory uncertainties brought about by the Digital Markets Act.”
The DMA places regulations on the tech giants that operate in the EU to promote competition, prevent monopolistic practices, and enhance user choice within the digital marketplace. Among other things, it asks companies to share data with third parties and prevents them from favouring their own products and services above their rivals.
Despite previously asserting that EU users would not have access to Apple Intelligence on any device, Apple’s beta 1 release notes for macOS Sequoia 15.1 and iOS 18.1 suggest otherwise, as spotted by 9to5Mac.
SEE: Apple WWDC Keynote: iOS 18, iPad OS 18 and macOS 15 Sequoia Coming in Fall
Beta versions of the operating systems have been available to developers since July 29. The accompanying macOS notes state, “Apple Intelligence is not currently available in China,” while the iOS notes say, “Apple Intelligence is not currently available in the EU or China.”
As such, EU-based developers with compatible Macs can download the beta version of macOS Sequoia 15.1 and try out Apple Intelligence, provided their device language is set to U.S. English.
They can also download the beta versions of iOS 18.1 or iPadOS 18.1 on their iPhone or iPad, but they cannot use Apple Intelligence on them. When the operating systems are made available to all EU Apple users, this may still be the case.
Apple declined to provide a comment about the differences in the release notes.
Why Apple could release Apple Intelligence to EU-based Mac users and still comply with the DMA
The distinction between releasing Apple Intelligence in the EU on macOS rather than iOS or iPadOS does, in fact, align with the DMA.
The Act’s requirements apply only to the 24 core platform services offered by the seven “gatekeeper” companies, including Alphabet, Amazon, Apple, Booking, ByteDance, Meta, and Microsoft.
Of these 24, only the App Store, Safari, iOS, and iPadOS are considered core platform services — not macOS. This is likely because its market share is relatively small compared to other operating systems, meaning it does not have the same level of control or influence over the market.
Therefore, in theory, Apple could release Apple Intelligence onto macOS Sequoia 15.1 in the EU without complying with the DMA requirements. It cannot do this with Apple Intelligence on iOS 18.1 and iPadOS 18.1 without facing a fine from the European Commission.
SEE: macOS 15 Sequoia Cheat Sheet: Release Date, Name, Features and More
It is unclear why Apple is refusing to alter Apple Intelligence to comply with the DMA on all devices
Apple remains tight-lipped about the specifics of its reluctance to alter Apple Intelligence, as well as iPhone Mirroring and SharePlay Screen Sharing, so they comply with the DMA. But the requirement to allow third-party companies to interoperate with them may be a contributing factor.
According to a statement that Apple spokesperson Fred Sainz provided to The Verge, the company is “concerned that the interoperability requirements of the DMA could force us to compromise the integrity of our products in ways that risk user privacy and data security.”
However, these interoperability requirements largely apply to messaging services rather than AIs like Apple Intelligence. Messaging platforms must allow users to communicate across different apps, and data must be easily transferable between services to comply with the DMA.
Speaking at the Forum Europa in June, Margrethe Vestager, the European Commissioner for Competition, said, “I find that very interesting that [Apple says] ‘we will now deploy AI where we’re not obliged to enable competition.’”
She described it as an “open declaration that they know 100% that this is another way of disabling competition where they have a stronghold already.” Were Apple to provide more detailed information about why having Apple Intelligence comply with the DMA would present a security issue, Vestager’s point could be quickly disproved.
Thomas Regnier, a European Commission spokesperson, told TechRepublic in an emailed statement, “The EU is an attractive market of 450 million potential users and has always been open for business for any company that wants to provide services in the European internal market.
“All companies are welcome to offer their services in Europe, provided that they comply with E.U. legislation.
“It is the companies’ responsibility to ensure that their services comply with our legislation.”
Must-read Apple coverage Withholding Apple Intelligence from EU users would have severe financial consequences — and Apple knows it
Many analysts expect that the inclusion of Apple Intelligence will drive consumers to upgrade their devices, as only the iPhone 15 Pro or Pro Max will be compatible initially.
Dan Ives, an analyst at Wedbush Securities, told Reuters he expects over 15% of iPhone users will upgrade to the yet-to-be-announced iPhone 16 “as Apple Intelligence is the killer app many have been waiting for.”
Furthermore, Europe accounts for over a quarter of Apple’s total revenue, so the loss of the region’s market upon the launch of Apple Intelligence would cost the company dearly. As such, the firm is still in communication with the European Commission to see if a solution can be found.
Last week, Apple CEO Tim Cook said on an investor call that Apple is “engaged” with regulators to make AI features available to “everyone” after being asked about the rollout of Apple Intelligence in both the EU and China, according to 9to5Mac.
Sainz’s statement to The Verge also said, “We are committed to collaborating with the European Commission in an attempt to find a solution that would enable us to deliver these features to our EU customers without compromising their safety.”
What is the Digital Markets Act?
The DMA, established in 2022, is an EU regulation that intends to promote fairness and competition among digital products and services. It established obligations for certain influential tech firms, dubbed “gatekeepers,” that must comply within their daily operations.
These cover:
Providing users access to the data gatekeepers collect about them. Tracking users outside their platforms. Allowing third parties to interoperate within their platforms. Allowing users to uninstall any pre-installed software or app. Deprioritising services and products offered by third parties on the gatekeeper’s platform.
Fines for noncompliance with the DMA can be up to 10% of the company’s total worldwide turnover, going up to 20% in cases of repeated infringement. In more extreme instances, the commission may order an organisation to sell all or parts of its business or ban the organisation from acquiring related services.
Last month, Apple became the first tech giant to be formally charged by the European Commission for violating the DMA.
The commission found that Apple has three sets of business rules that ultimately prevent iOS app developers from directing their users towards third-party purchase options. This goes against the DMA, which states that developers should be able to steer their customers toward purchasing options outside of the App Store easily and free of charge.
Why DataWalk is the Ideal, Affordable Alternative to Palantir for Intelligence Analysis
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In today’s data-driven world, the need for robust intelligence analysis tools is paramount. Organizations across various sectors are continually seeking solutions that not only provide comprehensive analytical capabilities but also come at a reasonable cost. DataWalk stands out as a compelling alternative to Palantir Gotham, offering similar functionality but at a significantly lower price point.
DataWalk is engineered to connect data from a wide array of internal and external sources, consolidating this information into a single knowledge graph. This allows for the seamless organization and categorization of data into understandable entities such as people, phone calls, transactions, and anything else. To ensure an accurate view of connected, consolidated data, DataWalk supports a powerful entity resolution facility.
These capabilities are particularly crucial for organizations that rely heavily on extensive data analysis and visualization, including tasks like link analysis, complex queries, machine learning, geospatial analysis, and entity extraction.
The design of the DataWalk platform ensures scalability, enabling it to handle vast amounts of data efficiently. This scalability is essential for large organizations or those dealing with significant data volumes. Furthermore, DataWalk supports collaborative efforts, allowing users to work together on investigations and share insights seamlessly across the organization.DataWalk is sufficiently easy to use that less technical users can effectively use the system, and this helps ensure that both analysts and other users across the organization can contribute effectively to the investigative and analytical processes.
One of the standout features of DataWalk is that it’s an open system. This design facilitates effortless interoperability with other systems, whether they are upstream or downstream in the data workflow. This interoperability is a critical component for supporting automated enterprise workflows, making DataWalk a versatile choice for various operational needs.
The DataWalk App Center is another notable aspect, allowing the integration of machine learning models, custom scripts, and specialized open-source software modules. This flexibility ensures that organizations can tailor the platform to their specific requirements without needing extensive custom development. Whether developed by DataWalk, its partners, or the customers themselves, these “apps” enhance the platform’s utility and adaptability.
DataWalk’s AI capabilities include a Machine Learning facility. This supports an end-to-end Machine Learning process in a single platform, accelerating time to production results, and enabling delivery of better results.
Recently the application of Large Language Models (LLMs) has become an imperative for many organizations, and DataWalk is a great supporting tool for LLMs. DataWalk integrates with various LLMs, and the knowledge graph makes a significant contribution toward ensuring that your LLMs deliver accurate results.
Cost is a significant differentiator between DataWalk and Palantir Gotham. The pricing for DataWalk starts at $43,000 per server core, which is a fraction of Palantir Gotham’s starting price of $141,000 per server core. This substantial cost difference makes DataWalk an attractive option for organizations who want something like Palantir Gotham, but simply cannot afford it.
Moreover, DataWalk’s business model is designed to be less services-intensive compared to Palantir’s. DataWalk offers Commercial Off The Shelf Software (COTS), maintaining a single code base and releasing new software updates roughly every quarter. This approach ensures that all customers benefit from the latest enhancements and features without incurring additional costs for custom development. DataWalk also empowers its customers to make modifications themselves, such as altering the data model or connecting new data sources, reducing the need for ongoing professional services.
In conclusion, DataWalk provides a robust, scalable, and cost-effective alternative to Palantir Gotham. Its comprehensive data integration and analysis capabilities, combined with its open platform and flexible integration options, make it an ideal choice for organizations seeking advanced tools for intelligence analysis, fraud detection, anti-money laundering, and other applications. The significant cost savings and customer-friendly business model further enhance DataWalk’s appeal, offering a practical solution for organizations needing powerful analytical tools without the high price tag associated with Palantir Gotham.
3 Artificial Intelligence Stocks with Promising Applications
InvestorPlace – Stock Market News, Stock Advice & Trading Tips
Artificial intelligence made headlines in 2024, with stocks in the space appreciating tremendously. Amid the growing adoption of technology, many companies are shelling out billions to advance their AI capabilities.
According to a recent report by CompTIA, 22% of companies aim to pursue AI integration across their products. The report also found that 33% of companies are working with some type of AI application to improve their service and product delivery.
By riding this wave, investors can be sure to see gains over the medium term. Artificial intelligence is still in its infancy, which means these stocks hold great potential. Numerous technology applications are still being explored.
For instance, it could have use cases in defense, chatbots and data analysis. Consider these three companies if you want to invest in solid artificial intelligence stocks with great promise in returns. Let’s examine why these three stocks stand out.
Nvidia (NVDA)
Nvidia (NASDAQ:NVDA) started as a graphics card company. However, its chips quickly became popular in the artificial intelligence sector. Since then, the company has been working to produce faster and more efficient chips for the industry.
CEO Jensen Huang has played an important role in this transformation, making Nvidia the go-to company for the best artificial intelligence chips.
Thus far, Huang’s efforts have paid off and Nvidia has been the top artificial intelligence stock of 2024. Despite sliding by double digits in the past few weeks, NVDA is still up 116.42% year. Over the past 12 months, the stock has gained 129.52%.
Looking at the EPS, Nvidia has continued to maintain phenomenal growth. In the last quarterly results, it reported an EPS of $5.98, a 629% year-over-year increase.
Its current trailing 12-month price-to-earnings ratio of 59.59 is relatively high. However, this high valuation is justifiable if it continues to maintain earnings growth.
Additionally, the company has a robust buyback program and pays out dividends. In its first quarter fiscal 2025 results, it announced it had increased payouts by 150% to 10 cents per share.
Over the past five years, NVDA has been one of the best-performing stocks, rising over 2500%.
The great stock performance, increased dividend payouts and the rising adoption of AI make Nvidia one of the best artificial intelligence stocks to own in August 2024.
Arista Networks (ANET)
Arista Networks (NYSE:ANET) is a leading software provider in the cloud computing and data center industries. The rise of artificial intelligence has been a huge boost for the company.
All artificial intelligence models require massive amounts of data, which is where Arista comes in. It is helping to create networks that can adapt to the changing needs of large language models and other artificial intelligence use cases.
Its stock performance has been quite robust. Year-to-date, it has gained 39.72% to $323.54 per share. In the past 12 months, its stock price has gained over 80%. If you had invested in ANET five years ago, you would have seen returns of almost 500% so far.
Its trailing 12-month price-to-earnings ratio of 42.69 is quite high. However, the stock has also maintained robust earnings growth. Its diluted earnings per share have steadily been on the rise since 2020. As a result, its elevated valuation is justifiable.
Looking at its financial results, Arista saw revenue rise 15.9% in the second quarter of fiscal 2024 to $1.69 billion. It also reported a GAAP net income of $665.4 million compared to $491.9 million the previous year.
Based on its robust financial and stock performance, ANET is one of the main artificial intelligence stocks that should be in your portfolio in August 2024.
Meta Platforms (META)
Meta Platforms (NASDAQ:META) is a giant tech company best known for its social media platforms, Instagram and Facebook. The company is also one of the leading investors in artificial intelligence.
One of its well-known products to date is Llama 3.1, an open-source artificial intelligence model. In its second quarter fiscal 2024 results, Meta revealed it plans to spend up to $40 billion on research, with a good chunk of that going to artificial intelligence.
Despite the huge capital expenditure, Meta reported astronomical profits with net income of $13.47 billion compared to $7.79 billion the previous year.
Investors have reacted positively to this increased spending with META up 42.68% this year and its value rising by 56% over the last 12 months.
Based on its robust financial results and rising expenditures on artificial intelligence, Meta could be the go-to investment for artificial intelligence stocks. It shows great promise and has the financial capacity to develop technology to the next level.
On the date of publication, Joel Lim did not have (either directly or indirectly) any positions in the securities mentioned in this article. The opinions expressed in this article are those of the writer, subject to the InvestorPlace.com Publishing Guidelines.
On the date of publication, the responsible editor did not have (either directly or indirectly) any positions in the securities mentioned in this article.
Joel Lim is a contributor at InvestorPlace.com and a finance content contractor who creates content for several companies like LTSE and Realtor, along with financial publications, including Business Insider, Yahoo Finance, Mises Institution and Foundation for Economic Education.
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10 AI business ideas for beginners getting started with artificial intelligence
Have you ever wondered how people are making money with AI? You might be interested in a new guide created by the team over at AIGRID that discussed 10 ways to actually make money using artificial intelligence for beginners. With the rapid advancements in technology, AI has opened up a wealth of opportunities for financial gain. Whether you’re interested in content creation, AI-generated art, or investing in AI stocks, this guide will provide you with ten actionable strategies to get started.
AI Business Ideas 2024
Key Takeaways :
AI offers numerous opportunities for financial gain, even for beginners. Content creation using AI tools can generate income through ad revenue and sponsorships. Starting an AI-focused newsletter can be profitable through subscriptions and sponsorships. AI-generated music can provide long-term revenue through royalties. AI design tools enable the creation and sale of unique art products. Developing custom AI automations can improve business efficiency and offer substantial rewards. Consulting services for AI integration are in high demand among businesses. Teaching AI tools and applications can be a rewarding business opportunity. Affiliate marketing of AI products can generate commissions and build audience trust. Investing in AI-related stocks offers significant growth potential. AI-related crypto projects present high-return investment opportunities. Focusing on niche markets and producing quality content are key strategies for monetizing AI.
Artificial intelligence (AI) presents numerous opportunities for financial gain, even if you’re just starting out. This guide outlines ten practical methods to monetize AI, offering detailed insights into various strategies, from content creation to investing in AI-related stocks. Whether you have a technical background or are simply curious about the potential of AI, these approaches can help you generate income and build a successful business.
Content Creation
Creating content is a lucrative way to leverage AI. You can produce engaging videos on popular platforms like YouTube, TikTok, and Instagram. AI tools can assist in various aspects of the content creation process, such as:
Editing videos to enhance their visual appeal and storytelling Generating scripts to streamline the writing process and ensure consistent quality Optimizing content for search engines to increase visibility and reach a wider audience
By focusing on ad revenue and sponsorships, you can generate a steady income from your AI-powered content. Additionally, launching niche communities around your content can provide recurring revenue through memberships and exclusive content, fostering a loyal and engaged audience.
Here are a selection of other articles from our extensive library of content you may find of interest on the subject of starting SaaS businesses :
Newsletter-Based Content
Starting an AI-focused newsletter can be highly profitable AI business idea. Specialized newsletters on topics like MidJourney or ChatGPT attract a dedicated audience eager to stay informed about the latest developments in AI. You can monetize these newsletters through subscriptions and sponsorships, providing valuable insights and resources to your readers. Successful newsletters can also be sold for significant profits, making this a viable long-term strategy for those passionate about AI and content creation.
AI tools enable you to create high-quality music tracks without extensive musical knowledge. Platforms like Spotify allow you to distribute your music widely, reaching a global audience. Over time, you can earn royalties from your tracks, providing a long-term revenue stream. This method is particularly appealing for those interested in the music industry but lacking traditional skills, as AI empowers them to express their creativity and build a successful career.
AI-Generated Art
AI design tools like MidJourney and Canva make it easy to create unique and visually stunning art. You can sell these designs as products through third-party sellers like Printery, tapping into the growing demand for AI-generated artwork. Focusing on niche markets can reduce competition and increase your chances of success, as you cater to specific tastes and preferences. This approach combines creativity with technology, offering a unique way to monetize AI and showcase your artistic vision.
AI automations can significantly improve business efficiency by streamlining repetitive tasks and optimizing workflows. Platforms like Zapier allow you to automate various processes, saving time and resources for businesses across industries. By targeting specific sectors and understanding their unique challenges, you can offer tailored solutions that meet their needs and deliver tangible results. This method requires some technical knowledge but offers substantial rewards for those willing to invest in developing their AI automation skills.
Providing AI integration advice is another profitable avenue. As businesses increasingly recognize the potential of AI to drive growth and innovation, they are seeking expertise to help them navigate this complex landscape. By offering consulting services, you can capitalize on this growing demand and help organizations harness the power of AI. Local businesses and startups are often in need of such expertise, making this a viable option for those with a background in AI and a keen understanding of its practical applications.
AI Education
Teaching AI tools and applications can be highly rewarding, both personally and financially. You can create courses or tutorials focused on niche AI tools, sharing your knowledge with a wide audience. Building a business around AI education allows you to make a positive impact while generating income, as you help others understand and harness the potential of AI. This method is ideal for those who enjoy teaching and have a deep understanding of AI technologies, as they can translate complex concepts into accessible and actionable insights.
Promoting AI products through affiliate marketing can generate commissions, providing a passive income stream. By focusing on high-quality products and recurring revenue models, you can maximize your earnings and build a sustainable business. It’s crucial to ensure the quality and relevance of the products you promote, as this helps build trust with your audience and establishes you as a reliable source of information. By consistently delivering value and promoting products that genuinely benefit your audience, you can achieve long-term success in affiliate marketing.
Monetizing AI offers numerous opportunities for beginners, regardless of their background or technical expertise. From content creation to investing in AI stocks, each method provides a unique way to generate income and build a successful business. By focusing on niche markets, producing quality content, and making strategic investments, you can leverage the power of AI for financial gain.
This AI business ideas guide offers a starting point and actionable steps to help you get moving on your AI monetization journey, empowering you to explore the vast potential of this transformative technology. As you embark on this exciting path, remember to continuously learn, adapt, and innovate, as the AI landscape continues to evolve at a rapid pace. With dedication, creativity, and a willingness to embrace change, you can harness the power of AI to achieve your financial goals and make a meaningful impact in the world.
Video Credit: AIGRID
Filed Under: AI, Top News
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Apple Intelligence EU: Potential Mac Release Amid DMA Rules
There is evidence that the EU may get Apple Intelligence after all — thanks to a tiny difference in the release notes for macOS Sequoia 15.1 and iOS 18.1. It was previously thought that the AI feature would not be available in the bloc on any Apple device due to the Digital Markets Act.
Apple Intelligence is a suite of generative AI capabilities to be integrated into the next generation of Apple devices running on iOS 18, iPadOS 18, and macOS Sequoia. Back in June, the Cupertino giant revealed that devices in the EU will not come with Apple Intelligence this year, via Bloomberg. This was due to “regulatory uncertainties brought about by the Digital Markets Act.”
The DMA places regulations on the tech giants that operate in the EU to promote competition, prevent monopolistic practices, and enhance user choice within the digital marketplace. Among other things, it asks companies to share data with third parties and prevents them from favouring their own products and services above their rivals.
Despite previously asserting that EU users would not have access to Apple Intelligence on any device, Apple’s beta 1 release notes for macOS Sequoia 15.1 and iOS 18.1 suggest otherwise, as spotted by 9to5Mac.
SEE: Apple WWDC Keynote: iOS 18, iPad OS 18 and macOS 15 Sequoia Coming in Fall
Beta versions of the operating systems have been available to developers since July 29. The accompanying macOS notes state, “Apple Intelligence is not currently available in China,” while the iOS notes say, “Apple Intelligence is not currently available in the EU or China.”
As such, EU-based developers with compatible Macs can download the beta version of macOS Sequoia 15.1 and try out Apple Intelligence, provided their device language is set to U.S. English.
They can also download the beta versions of iOS 18.1 or iPadOS 18.1 on their iPhone or iPad, but they cannot use Apple Intelligence on them. When the operating systems are made available to all EU Apple users, this may still be the case.
Apple declined to provide a comment about the differences in the release notes.
Why Apple could release Apple Intelligence to EU-based Mac users and still comply with the DMA
The distinction between releasing Apple Intelligence in the EU on macOS rather than iOS or iPadOS does, in fact, align with the DMA.
The Act’s requirements apply only to the 24 core platform services offered by the seven “gatekeeper” companies, including Alphabet, Amazon, Apple, Booking, ByteDance, Meta, and Microsoft.
Of these 24, only the App Store, Safari, iOS, and iPadOS are considered core platform services — not macOS. This is likely because its market share is relatively small compared to other operating systems, meaning it does not have the same level of control or influence over the market.
Therefore, in theory, Apple could release Apple Intelligence onto macOS Sequoia 15.1 in the EU without complying with the DMA requirements. It cannot do this with Apple Intelligence on iOS 18.1 and iPadOS 18.1 without facing a fine from the European Commission.
SEE: macOS 15 Sequoia Cheat Sheet: Release Date, Name, Features and More
It is unclear why Apple is refusing to alter Apple Intelligence to comply with the DMA on all devices
Apple remains tight-lipped about the specifics of its reluctance to alter Apple Intelligence, as well as iPhone Mirroring and SharePlay Screen Sharing, so they comply with the DMA. But the requirement to allow third-party companies to interoperate with them may be a contributing factor.
According to a statement that Apple spokesperson Fred Sainz provided to The Verge, the company is “concerned that the interoperability requirements of the DMA could force us to compromise the integrity of our products in ways that risk user privacy and data security.”
However, these interoperability requirements largely apply to messaging services rather than AIs like Apple Intelligence. Messaging platforms must allow users to communicate across different apps, and data must be easily transferable between services to comply with the DMA.
Speaking at the Forum Europa in June, Margrethe Vestager, the European Commissioner for Competition, said, “I find that very interesting that [Apple says] ‘we will now deploy AI where we’re not obliged to enable competition.’”
She described it as an “open declaration that they know 100% that this is another way of disabling competition where they have a stronghold already.” Were Apple to provide more detailed information about why having Apple Intelligence comply with the DMA would present a security issue, Vestager’s point could be quickly disproved.
Thomas Regnier, a European Commission spokesperson, told TechRepublic in an emailed statement, “The EU is an attractive market of 450 million potential users and has always been open for business for any company that wants to provide services in the European internal market.
“All companies are welcome to offer their services in Europe, provided that they comply with E.U. legislation.
“It is the companies’ responsibility to ensure that their services comply with our legislation.”
Must-read Apple coverage Withholding Apple Intelligence from EU users would have severe financial consequences — and Apple knows it
Many analysts expect that the inclusion of Apple Intelligence will drive consumers to upgrade their devices, as only the iPhone 15 Pro or Pro Max will be compatible initially.
Dan Ives, an analyst at Wedbush Securities, told Reuters he expects over 15% of iPhone users will upgrade to the yet-to-be-announced iPhone 16 “as Apple Intelligence is the killer app many have been waiting for.”
Furthermore, Europe accounts for over a quarter of Apple’s total revenue, so the loss of the region’s market upon the launch of Apple Intelligence would cost the company dearly. As such, the firm is still in communication with the European Commission to see if a solution can be found.
Last week, Apple CEO Tim Cook said on an investor call that Apple is “engaged” with regulators to make AI features available to “everyone” after being asked about the rollout of Apple Intelligence in both the EU and China, according to 9to5Mac.
Sainz’s statement to The Verge also said, “We are committed to collaborating with the European Commission in an attempt to find a solution that would enable us to deliver these features to our EU customers without compromising their safety.”
What is the Digital Markets Act?
The DMA, established in 2022, is an EU regulation that intends to promote fairness and competition among digital products and services. It established obligations for certain influential tech firms, dubbed “gatekeepers,” that must comply within their daily operations.
These cover:
Providing users access to the data gatekeepers collect about them. Tracking users outside their platforms. Allowing third parties to interoperate within their platforms. Allowing users to uninstall any pre-installed software or app. Deprioritising services and products offered by third parties on the gatekeeper’s platform.
Fines for noncompliance with the DMA can be up to 10% of the company’s total worldwide turnover, going up to 20% in cases of repeated infringement. In more extreme instances, the commission may order an organisation to sell all or parts of its business or ban the organisation from acquiring related services.
Last month, Apple became the first tech giant to be formally charged by the European Commission for violating the DMA.
The commission found that Apple has three sets of business rules that ultimately prevent iOS app developers from directing their users towards third-party purchase options. This goes against the DMA, which states that developers should be able to steer their customers toward purchasing options outside of the App Store easily and free of charge.