Рубрика: AI

The use of artificial intelligence by movie and TV studios to generate story ideas and scripts is one reason the Writer's Guild of America went on strike in the spring of 2023. The writers are smart to be concerned, but according to Greg Harrison, chief creative officer at MOCEAN, a creative agency that works with firms like Netflix, Paramount, and Marvel, generative AI technology presents opportunities and challenges for creative professionals.

Also: ChatGPT's intelligence is zero, but it's a revolution in usefulness, says AI expert

When AI tools like Midjourney and ChatGPT emerged, there was a sense of alarm at their promise to generate creative content. But as Harrison and his team explored these and many other AI tools, they concluded that AI is not ready to replace human creativity. It's still a fledgling technology that needs guidance and mentorship, much like a junior creative team member.

"I think that it can be a source of inspiration, it can be a source of investigation," Harrison said. "The ability to summarize material and look for themes is powerful. We found that in playing with it, we can see the beginnings of the potential for it to be a collaborator. A lot of people throw around the term 'copilot,' and I think that feels right. It's got enough knowledge, and under a certain focused inquiry, it can produce inspiration for our creatives."

Harrison envisions AI as a tool, providing a source of inspiration and investigation, particularly when handling large bodies of material and seeking themes. He emphasizes the need to demystify AI and to see it for what it is — a tool, not an emerging super-intelligent being. This viewpoint aids in managing the fear and concern surrounding AI and its implications for creative jobs.

That said, AI poses concerns, particularly regarding copyright and ethics. Generative AI is trained on large volumes of copyrighted imagery, which could lead to inadvertent infringement issues. Without a clear chain of titles or a clean and ethical training base, using such technology in a professional setting becomes challenging. Solutions like Firefly, Adobe's generative AI tool, are a step in the right direction.

Also: The 5 biggest risks of generative AI, according to an expert

In the near future, AI will be a collaborator, a source of inspiration under the direction of a creative director. The technology's potential as a tool for visual brainstorming, exploration, and possibly even creating final outputs is promising as long as it remains under human control. This could also lower the cost of complex visual effects or high-end 3D designs, opening new doors for creative ambitions.

However, AI's role in the creative industry isn't solely in generating content. It could also contribute by automating non-creative tasks, liberating time for creatives to focus on their craft.

If integrating AI into a creative workflow, Harrison advises a cautious approach. He emphasizes the importance of valuing human creativity and culture and letting that guide one's engagement with AI. In the short term, AI tools are best used for exploration, inspiration, and visual reference. It is crucial to experiment with them and understand their current limitations while examining their future potential.

Also: Meet the post-AI developer: More creative, more business-focused

"When used correctly, it can free creatives to focus time and energy on creative tasks, which has value," Harrison said.

The convergence of AI and creativity presents an intriguing landscape for creative industries. Whether viewed as a tool, threat, or collaborator, the future of AI in these industries is ripe with possibilities. As we navigate this landscape, the focus should remain on preserving human creativity and culture, fostering collaboration, and maximizing the opportunities AI offers.

Artificial Intelligence

Since its release, every day, around a lakh people on the internet use Midjourney, the AI art generating tool for the first time. But the fame is fading out dramatically. The first major impact came when the platform stopped free trials. Another reason for the loss of fame is that the platform is not intuitive to use as it can only be accessed through Discord. The task of jumping through all the hoops from ‘getting Discord, joining the beta, signing up, and then landing on the Discord server’ is repelling for users.

It’s been more than a year since the launch of Midjourney and the tool still does not give users the option like others to directly sign up, pay, prompt and get results. Users have long sought a custom UX with a prompt builder along with pull-down menus (to choose style, render quality, etc.).

While users were trying to ease the pain-in-neck process on Midjourney through bots, a few former Googlers noticed the uncharted territory.

This month, the team introduced Ideogram AI, a text-to-image tool similar to Midjourney.

While the market is already dominated by Midjourney, Adobe’s Firefly, and OpenAI’s Dalle-2, et al. users claim Ideogram’s model has reliable text generation, which could give the new entrant an edge for generating logos. In fact, Ideogram’s ‘superfast powerful brain going to the right’ logo was also generated by the platform!

Did you know our logo is a super fast powerful brain going to the right?
Do you have a guess who generated the logo? pic.twitter.com/yHpBxNfynX

— Ideogram (@ideogram_ai) August 25, 2023

Nevin Thomas, creative head at AIM experiments with such AI tools regularly. His LinkedIn post based on his latest experiment with Ideogram reads, “Where one AI tool fails another shines! #Midjourney is miles better than Ideogram (at this stage at least) when it comes to generating images from text prompts but Ideogram seems to be ahead when it comes to putting text on the image.” He prompted Midjourney and Ideogram with the same text description — Astronauts at a space station holding a sign that says, “WE ARE HERE”, photo.

The result shows a startling difference between the two AI-powered platforms in understanding the prompts. Moreover, Ideogram runs in the browser and directly integrates social media features making it easier for users like Thomas to explore tools alike.

Developed by three former Google research scientists — Chitwan Saharia, William Chan, and Jonathan Ho, who have worked on the tech goliath’s AI projects such as Imagen, Google’s own text-to-image system. The team launched the platform backed by A16z and others with $16.5m in seed financing to develop state-of-the-art tools.

The (Legal) Rabbit Hole

Artificial intelligence has been having a tryst with art for quite some time. From restoring Klimt’s legendary ‘Trio’ to Midjourney’s game-changing generative AI fill the art-tech community has come a long way within a few years. While AI art has encouraged users to create 15+ billion images within months, the tools are constantly being raised fingers at by ethicists and art connoisseurs.

For instance, Sarah Andersen, Kelly McK­er­nan, and Karla Ortiz dragged Midjourney, Deviant Art and Stability.AI to court for using their work without consent. Even though the heap of accusations has been lengthening, the laws are in favour of these tools.

Welp, didn’t take long for DALL-E to pivot to paid model and DOR has summed up pretty succinctly how that’s a problem pic.twitter.com/8NLSwS437L

— Dan Kelly (@dananthonykelly) July 22, 2022

As a result, people like David Holz, founder of Midjourney “don’t really wanna be involved in” the plagiarism issues that haunt the internet. Pointing at his relaxed view on data theft, John Oliver quipped, saying, “I am not really surprised. He looks like hipster Willy Wonka answering a question on whether importing Oompa Loompas makes him a slave owner.”

While all sorts of thorny legal questions are being raised at these dreamy art generators, Adobe is confident that its Firefly won’t breach any copyright laws. The design software provider is so sure that it guarantees to compensate businesses if they’re sued for infringement over any image its tool creates.

For its part, Ideogram states that it has a focus on creativity with a “high standard for trust and safety.” The latest contender has become successful overnight as users are already testing typography with its skills. Moreover, OpenAI’s Andrej Karpathy and Cohere’s co-founder Nick Frosst are some of the first followers of the tool’s social media page. While the tool has just gotten into the hands of users, we wait to see how long the ball lasts in Ideogram’s court.

The post The Ball is in Ideogram’s Court, While Midjourney Sticks To Discord appeared first on Analytics India Magazine.

Indian Prime Minister Narendra Modi, while speaking at the Responsible AI for Social Empowerment (RAISE) 2020 summit, said he wants the country to become an AI hub, however, one of the major drivers of AI, besides data, is compute. For example, the supercomputer hosted in Microsoft Azure, specifically designed for OpenAI, incorporates thousands of NVIDIA Graphics Processing Units (GPUs) to power AI workloads and accelerate training processes. But, currently, the global AI industry is facing a shortage of these GPUs.

Moreover, today not just AI labs but different organisations and countries are trying to get their hands on these GPUs. The UK Prime Minister Rishi Sunak is planning to spend USD 126.3 million to buy AI chips as a part of the country’s plans to improve its AI resources and become a leader in AI. Reportedly, the company is already in talks with major AI chip makers such as NVIDIA, AMD and Intel.

The market shortage is significant to the extent that even NVIDIA’s planned production of 2 million GPUs for 2024 is already sold out. Given India’s own ambitions in AI, the shortage could have both short-term and long-term implications for India. Moreover, owing to the intricate nature of GPUs, they can become entwined with geopolitics. For instance, the US government’s imposition of export controls prevents NVIDIA from selling its AI chips to China. Considering the industry’s heavy dependence on NVIDIA’s near-monopoly in the GPU market, amassing GPUs, like the UK, might emerge as a rational move for India.

Will the GPU crisis impact India companies

In India, there are numerous startups and large organisations working on or deploying AI models at different levels. Today we are in the age of generative AI. Its explosive growth, which involves training complex models that require significant computational power, has led to a surge in demand for AI-focused GPUs. In India, a host of companies have built or are in the process of building proprietary Large Language Models (LLM).

Leena AI, which is a conversational AI-backed platform, has developed WorkLM, the company’s proprietary LLM built especially for enterprise employee experience. In a previous interaction with AIM, Mayank Kumar, co-founder & managing director at upGrad said that the edtech firm is exploring the idea of building its own proprietary LLM. Similarly, Indian IT giant Tech Mahindra is already building an Indic-LLM that would have the ability to converse in over 40 Indic languages.

Moreover, there are over 4000 AI startups in India, according to Tracxn. Given the number will only increase in the coming years, the computing power required to train models will also increase significantly. Even though Indian firms can rely on hyperscalers like AWS and Azure for computational power, buying GPUs brings significant advantages. In such a case, larger companies may find it relatively easier to acquire GPUs, but smaller businesses might face challenges in obtaining them. Pawan Prabhat co-founder of Shorthills AI believes the government buying GPUs might not be the right idea because, historically, India has done better in sectors where the government has had less control. “Rather it can help software companies offset the increased costs by giving some tax exemptions on purchases of GPUs physically or in the cloud for a limited period. Just like we have tax policies and SOPs to support startups, the government can be of help indirectly,” he told AIM.

However, Ranjan Chopra, managing director and chief executive officer at Team Computers believes the Indian government should consider allocating funds to acquire GPUs to advance its AI ambitions. If the government makes such an investment, it would align perfectly with India’s vision for technological leadership, fostering innovation, driving economic growth, and ensuring competitiveness in the global AI landscape. “Such a strategic investment not only accelerates AI progress but can also position India as an innovative powerhouse, supporting startups, fostering economic growth, and strengthening our global AI leadership,” he told AIM.

GPUs are the backbone of AI Research

Moreover, for India to achieve leadership in AI, it must place a substantial emphasis on AI research, a critical component of which is GPUs. The government has established the National Research Foundation (NRF) with the aim of enhancing research efforts in the nation, including the field of AI research. In a previous interaction with AIM, Prof. Arnab Bhattacharya, Dept of Computer Science & Engineering, IIT Kanpur, said that AI researchers in India often struggle with funds required to buy hardware such as GPUs/TPUs.

Currently, there are AI supercomputers like AIRAWAT, powered by NVIDIA DGX A100 GPUs, empowering researchers in India. Nonetheless, in the future, the demand for computational power is anticipated to increase significantly. In this light, the government has announced plans to develop nine more supercomputers in the country. However, the requirement for supercomputers in the country is diverse, hence, we can hope a portion of the new supercomputers will be dedicated towards AI research.

Kesava Reddy, CRO at E2E Networks told AIM that ​​the government can explore strategies like bulk purchasing to subsidise the cost of GPUs for research and development purposes. “Potentially a PPP (Public-Private Partnership) model can be explored to make GPUs more accessible and affordable for AI research. This can potentially be done in collaboration with local Cloud Service Providers (CSPs), who enable the Indian market and are being used by local startups and enterprises.”

Furthermore, startups who are building generative AI technologies can also benefit from this, and get leverage in a highly competitive global landscape. “Using money to get GPUs can help Indian AI startups and research projects have the right tools for their work. But we should also aim to make GPUs here in India, so we don’t have to rely on others in the long term,” Vaibhav Srivastava, senior information security analyst/ marketing Lead at Innefu Labs, told AIM.

Making India self-reliant

AI is pervasive and going forward, the use cases of the technology are going to multiply. Similar to India’s focus on becoming self-reliant in semiconductors, the question that arises is should India aim to become self-reliant in AI hardware as well? Similar to the US-China scenario, if tomorrow, the US forbids NVIDIA from shipping chips to India, it could become a potential crisis.

Hence, “I strongly advocate that India should prioritise the local production of GPUs and AI chips, akin to the strategic focus on semiconductor manufacturing. Local production offers several strategic advantages. Firstly, it reduces India’s reliance on international markets, ensuring a more dependable supply. Recent global supply chain disruptions underscore the need for self-reliance in critical technology components,” Chopra said.

Reddy also believes with India’s focus on ‘Make in India’, and local manufacturing, building a domestic industry for GPUs and AI chips can be a powerful long-term strategy. Much like the USD 10 billion Production-Linked Incentive (PLI) scheme for semiconductors, the government could entice industry giants such as NVIDIA and AMD to establish manufacturing units within the nation.

But Prabhat, on the other hand, is of the opinion that making a GPU or an AI chip at this point in time will be a tall order. India is trying its hand at creating a fab and it might not be a good idea to get into creating AI hardware right now. “India has traditionally been very strong in software and given that we are also far off from creating a cloud infrastructure company like AWS, Azure, etc., it might be a better idea to collaborate with these chip companies and cloud companies to help them set up their units in India. In due time, we can also create our own GPU/ AI chips.” But in the short-term, the biggest leverage would potentially come from figuring out ways through which local startups and businesses can access advanced GPUs, Reddy said.

The post Could the GPU Crisis Put India’s Innovation at Stake? appeared first on Analytics India Magazine.

AI safety and bias are urgent yet complex problems for safety researchers. As AI is integrated into every facet of society, understanding its development process, functionality, and potential drawbacks is paramount.

Lama Nachman, director of the Intelligent Systems Research Lab at Intel Labs, said including input from a diverse spectrum of domain experts in the AI training and learning process is essential. She states, "We're assuming that the AI system is learning from the domain expert, not the AI developer…The person teaching the AI system doesn't understand how to program an AI system…and the system can automatically build these action recognition and dialogue models."

Also: World's first AI safety summit to be held at Bletchley Park, home of WWII codebreakers

This presents an exciting yet potentially costly prospect, with the possibility of continued system improvements as it interacts with users. Nachman explains, "There are parts that you can absolutely leverage from the generic aspect of dialogue, but there are a lot of things in terms of just…the specificity of how people perform things in the physical world that isn't similar to what you would do in a ChatGPT. This indicates that while current AI technologies offer great dialogue systems, the shift towards understanding and executing physical tasks is an altogether different challenge," she said.

AI safety can be compromised, she said, by several factors, such as poorly defined objectives, lack of robustness, and unpredictability of the AI's response to specific inputs. When an AI system is trained on a large dataset, it might learn and reproduce harmful behaviors found in the data.

Biases in AI systems could also lead to unfair outcomes, such as discrimination or unjust decision-making. Biases can enter AI systems in numerous ways; for example, through the data used for training, which might reflect the prejudices present in society. As AI continues to permeate various aspects of human life, the potential for harm due to biased decisions grows significantly, reinforcing the need for effective methodologies to detect and mitigate these biases.

Also: 4 things Claude AI can do that ChatGPT can't

Another concern is the role of AI in spreading misinformation. As sophisticated AI tools become more accessible, there's an increased risk of these being used to generate deceptive content that can mislead public opinion or promote false narratives. The consequences can be far-reaching, including threats to democracy, public health, and social cohesion. This underscores the need for building robust countermeasures to mitigate the spread of misinformation by AI and for ongoing research to stay ahead of the evolving threats.

Also: These are my 5 favorite AI tools for work

With every innovation, there is an inevitable set of challenges. Nachman proposed AI systems be designed to "align with human values" at a high level and suggests a risk-based approach to AI development that considers trust, accountability, transparency, and explainability. Addressing AI now will help assure that future systems are safe.

Artificial Intelligence

OpenAI has now unexpectedly become enterprise friendly. The creator of ChatGPT recently announced that it has chosen the San Francisco based data labelling company, Scale AI as its preferred partner to fine-tune GPT-3.5 for enterprises. This development came a day after OpenAI announced that fine-tuning for GPT 3.5 Turbo API is now available and the same facility for GPT-4 is coming this fall.

Scale, founded in 2016 by Alexander Wang and Lucy Guo, helps enterprises in building their own models or applying foundation models to their business, through data labelling and reinforcement learning with human feedback (RLHF). The company claims that its product Data Scale engine improves enterprise models by improving the data quality.

In their recent blog post where Scale AI announced its partnership with OpenAI, the company highlighted its prior collaboration with Brex, an American financial service and technology company. In this collaboration, Scale AI fine-tuned the GPT-3.5 API using Brex’s data, which was annotated with Scale’s Data Engine. The company claimed that results were remarkable and the fine-tuned GPT-3.5 model consistently outperformed the stock GPT-3.5 turbo model in 66% of cases.

OpenAI in the blog post said that Scale customers can now fine-tune OpenAI models just as they would through OpenAI, while also benefiting from Scale’s enterprise AI expertise and Data Engine. By making this move, OpenAI will also get access to Scale’s customers, which means the company will make more profit.

OpenAI’s announcements recently were all about fine-tuning the APIs of the existing models GPT-3, GPT-3.5, GPT-3.5 Turbo and GPT-4. On the other hand, the company had always been hell-bent towards achieving its AGI goals. For enterprise, Microsoft had been the key player all this while. When Microsoft made a multi-billion dollar investment in OpenAI at the beginning of the year, it was made clear that Azure will remain the exclusive cloud provider for all OpenAI workloads across research, API and products.

On the other hand, Scale is not a cloud provider, but it will allow enterprises to get access to OpenAI’s GPT-3.5 to fine-tune it. At the moment, the features provided by Scale AI are already accessible through Azure OpenAI service, including customisation of models using their own training dataset. Something’s surely fishy.

All not well with Microsoft?

In the last two weeks, there have been enough indications that things are not going so well between Microsoft and OpenAI. The Information’s latest report about Microsoft deciding to partner with Databricks was the final nail in the coffin.

The report said Microsoft is planning to sell a new version of Databricks’ software that helps customers make AI apps for their businesses. The tech giant plans to sell it through its Azure cloud-server unit, which will help companies make AI models from scratch or repurpose open-source models as an alternative to licensing OpenAI’s proprietary ones.

As a consequence, certain Microsoft clients might find themselves utilising open-source models rather than the closed-source alternatives from OpenAI, as data privacy with OpenAI’s models is a constant concern for many companies.

This move by Microsoft hinted that it is moving away from OpenAI and looking out for more partners which can help them make their Azure cloud services better for enterprises. To counter that, OpenAI is now also offering similar services on the Scale’s platform through which enterprises will be able to mould models according to requirements and on personal data.

OpenAI making up for the absence of GPT-5?

Earlier this month, OpenAI filed a trademark for GPT-5. Given the GPU shortage in Silicon Valley, it is still questionable about how the model is going to get built. Possibly, by announcing fine-tuning for its existing models, OpenAI is stalling the release of GPT-5 and making up for its absence.

Furthermore, OpenAI’s Logan Kilpatrick recently took to X and said that he is carving out time in the next two weeks to try and help improve GPT-4 and 3.5. “Please share examples of the model not performing well, the more details the better” he asked his followers, indicating OpenAI’s current focus is not GPT-5, rather improving existing models.

The company hasn’t been able to make GPT-4 multimodal yet, which it promised would happen during the announcement. Currently, OpenAI is just trying to grab enterprise’s attention as it is not able to please its regular customers with ChatGPT.

OpenAI teaming up with Scale AI means they’re venturing into a different direction and stepping away from their pet product, ChatGPT.

It has been 10 months since it was released and right now the harsh reality is that it has become stagnant with nothing new to offer to the users. There have been reports clearly indicating a decline in users.

OpenAI hasn’t been able to upgrade it with real time data yet, its information is still limited to September 2021. Also, there is absolutely no idea what is going on with plugins and the plugins store. Interestingly, Sam Altman had made it clear earlier that OpenAI would not release more products beyond ChatGPT.

For OpenAI, the best option to make money and continue existing is to focus on serving businesses. For that, the partnership with Scale AI makes a lot of sense.

The post The Real Reason Why OpenAI Partnered with Scale appeared first on Analytics India Magazine.

Open-source AI is rapidly reshaping the software ecosystem by making AI models and tools accessible to organizations. This is leading to a number of benefits, including accelerated innovation, improved quality, and lower costs.

According to the 2023 OpenLogic report, 80% of organizations are using more open-source software compared to 77% last year to access the latest innovations, improve development velocity, reduce vendor lock-in, and minimize license costs.

The current landscape of open-source AI is still evolving. Tech giants such as Google (Meena, Bard, and PaLM), Microsoft (Turing NLG), and Amazon Web Services (Amazon Lex) have been more cautious in releasing their AI innovations. However, some organizations, such as Meta and other AI-based research companies, are actively open-sourcing their AI models.

Moreover, there is an intense debate over open-source AI that revolves around its potential to challenge big tech. This article aims to provide an in-depth analysis of the potential benefits of open-source AI and highlight the challenges ahead.

Pioneering Advancements – The Potential of Open-Source AI

Many practitioners consider the rise of open-source AI to be a positive development because it makes AI more transparent, flexible, accountable, affordable, and accessible. But tech giants like OpenAI and Google are very cautious while open-sourcing their models due to commercial, privacy, and safety concerns. By open-sourcing, they may lose their competitive advantage, or they would have to give away sensitive information regarding their data and model architecture, and malicious actors may use the models for harmful purposes.

However, the crown jewel of open-sourcing AI models is faster innovation. Several notable AI advancements have become accessible to the public through open-source collaboration. For instance, Meta made a groundbreaking move by open-sourcing their LLM model LLaMA.

As the research community gained access to LLaMA, it catalyzed further AI breakthroughs, leading to the development of derivative models like Alpaca and Vicuna. In July, Stability AI built two LLMs named Beluga 1 and Beluga 2 by leveraging LLaMA and LLaMA 2, respectively. They showcased better results on many language tasks like reasoning, domain-specific question-answering, and understanding language subtleties compared to state-of-the-art models at that time. Recently, Meta has introduced Code LLaMA–an open-source AI tool for coding that has outperformed state-of-the-art models on coding tasks – also built on top of LLaMA 2.

Code LLaMA performance comparison

Researchers and practitioners are also enhancing the capabilities of LLaMA to compete with proprietary models. For instance, open-source models like Giraffe from Abacus AI and Llama-2-7B-32K-Instruct from Together AI are now capable of handling 32K long input context lengths – a feature that was only available in proprietary LLM like GPT-4. Additionally, industry initiatives, such as MosaicML's open-source MPT 7B and 30B models, are empowering researchers to train their generative AI models from scratch.

Overall, this collective effort has transformed the AI landscape, fostering collaboration and knowledge-sharing that continue to drive groundbreaking discoveries.

Benefits of Open-Source AI for Companies

Open-source AI offers numerous benefits, making it a compelling approach in artificial intelligence. Embracing transparency and community-driven collaboration, open-source AI has the potential to revolutionize the way we develop and deploy AI solutions.

Here are some benefits of open-source AI:

• Rapid Development: Open-source AI models allow developers to build upon existing frameworks and architectures, enabling rapid development and iteration of new models. With a solid foundation, developers can create novel applications without reinventing the wheel.
• Increased Transparency: Transparency is a key feature of open-source, providing a clear view of the underlying algorithms and data. This visibility reduces bias and promotes fairness, leading to a more equitable AI environment.
• Increased Collaboration: Open-source AI democratized AI development, which promotes collaboration, fostering a diverse community of contributors with varying expertise.

Navigating Challenges – The Risks of Open-Sourcing AI

While open-source offers numerous advantages, it is important to be aware of the potential risks it may entail. Here are some of the key concerns associated with open-source AI:

• Regulatory Challenges: The rise of open-source AI models has led to unbridled development with inherent risks that demand careful regulation. The sheer accessibility and democratization of AI raise concerns about its potential malicious use. According to a recent report by SiliconAngle, some open-source AI projects use generative AI and LLMs with poor security, putting organizations and consumers at risk.
• Quality Degradation: While open-source AI models bring transparency and community collaboration, they can suffer from quality degradation over time. Unlike closed-source models maintained by dedicated teams, the burden of upkeep often falls on the community. This often leads to potential neglect and outdated model versions. This degradation might hinder critical applications, endangering user trust and overall AI progress.
• AI Regulation Complexity: Open-sourcing AI models introduce a new level of complexity for AI regulators. There are a number of factors to consider, such as how to protect sensitive data, how to prevent models from being used for malicious purposes, and how to ensure that models are well-maintained. Hence, it is quite challenging for AI regulators to ensure that open-source models are used for good and not for harm.

The Evolving Nature of Open-Source AI Debate

“Open source drives innovation because it enables many more developers to build with new technology. It also improves safety and security because when software is open, more people can scrutinize it to identify and fix potential issues”, said Mark Zuckerberg when he announced the LLaMA 2 large language model in July this year.

On the other hand, major players like Microsoft-backed OpenAI and Google are keeping their AI systems closed. They are aiming to gain a competitive advantage and minimize the risk of AI misuse.

OpenAI’s co-founder and chief scientist, Ilya Sutskever, told The Verge, “These models are very potent and they’re becoming more and more potent. At some point, it will be quite easy, if one wanted, to cause a great deal of harm with those models. And as the capabilities get higher, it makes sense that you don’t want to disclose them.” So, there are potential risks related to open-source AI models that humans cannot ignore.

While AIs capable of causing human destruction may be decades away, open-source AI tools have already been misused. For example, the first LLaMA model was only released to advance AI research. But malicious agents used it to create chatbots that spread hateful content like racial slurs and stereotypes.

Maintaining a balance between open AI collaboration and responsible governance is crucial. It ensures that AI advancements remain beneficial to society while safeguarding against potential harm. The technology community must collaborate to establish guidelines and mechanisms that promote ethical AI development. More importantly, they must take measures to prevent misuse, enabling AI technologies to be a force for positive change.

Want to enhance your AI IQ? Navigate through Unite.ai‘s extensive catalog of insightful AI resources to amplify your knowledge.

To counter CMA (Competition and Markets Authority) blocking Microsoft – Activision Blizzard acquisition, Microsoft struck a deal with Ubisoft to give them the non-exclusive cloud streaming rights for Call of Duty and every other Activision Blizzard game for the next 15 years.

In January 2022, Microsoft bought Activision Blizzard for a whopping $68.7 billion. The troubles were only beginning for the approval of the largest tech deal ever as Microsoft has had to jump several hoops to retain the deal. First they faced the Federal Trade Commission (FTC) who lost the appeal in the US court to pause the merger. The UK’s equivalent – Competition and Markets Authority (CMA), however, rejected the arguments against Microsoft and has successfully blocked the merger sticking to its original decision in April.

To appease the CMA Microsoft two days ago announced that they would not acquire the cloud streaming rights to all current Activision games and the and future releases for the next 15 years (excluding in the European Economic Area [EEA]). Instead the cloud streaming rights will be divested to Ubisoft prior to Microsoft’s acquisition of Activision.

“Ubisoft will compensate Microsoft for the cloud streaming rights to Activision Blizzard’s games through a one-off payment and through a market-based wholesale pricing mechanism, including an option that supports pricing based on usage,” explained Brad Smith, the Vice Chairman of Microsoft. “It will also give Ubisoft the opportunity to offer Activision Blizzard’s games to cloud gaming services running non-Windows operating systems.”

After this announcement the CMA has again launched an investigation on this new restructure.

CMA succeeds where FTA failed

The FTC’s case was that the deal would unfairly harm competition in the gaming market and insisted that Microsoft was going to remove Call of Duty from Playstation if the acquisition came to fruition. The judge shot down the claims citing lack of evidence. The CMA took a different route where they questioned Microsoft’s dominance in the nascent cloud market after the acquisition.

Microsoft said, “Today we have notified the restructured transaction to the CMA and anticipate that the CMA review processes can be completed before the 90-day extension in its acquisition agreement with Activision Blizzard expires on October 18.”

Both FTC and CMA’s intentions, though good, isn’t making any difference in this case as the cloud streaming space is very small yet accounting for only 890 million and the major players are Nvidia, Nintendo, Sony and Ubisoft.

But, Microsoft found a way

The Microsoft-Ubisoft partnership is a roundabout way for Microsoft to access the cloud rights without really owning it. The alliance was only to address the concerns of the regulators and wouldn’t really make a difference to the gamers. While some say it is a win for consumers as it means you won’t need to buy an Xbox to play Activision games since they’ll be available cross-platform anyway.

Activision and Blizzard merged way back in 2008, together they make some of the most played games including Call of Duty, Candy Crush, Warcraft, Diablo etc. Microsoft’s pursuit of the Activision deal is driven by its ambition to solidify its standing in the gaming industry. Although currently ranked third globally this strategic move would position Microsoft to contend fiercely with major players like Sony, granting the company a potent foothold in the gaming arena.

Over the years, Microsoft has focused on building their foothold on games that don’t require high powered devices, instead consumers can use their phones and laptop. With this acquisition, Microsoft is reinforcing the idea that games can be played on all sorts of devices as Activision Blizzard has plenty of options.

A crucial facet of this endeavor is the reinforcement of Xbox Game Pass, Microsoft’s subscription service that offers gamers access to a library of titles. The integration of Activision’s games into the service would render Xbox Game Pass even more alluring, leading to an expansion of its already large subscriber base. This aligns with Microsoft’s goal of providing gamers with a comprehensive and attractive gaming experience.

Ubisoft with this new licensing agreement will allow Microsoft to sell the cloud gaming rights for current and future Activision Blizzard games to Ubisoft. This means that Ubisoft will be able to stream Activision Blizzard games on its own cloud gaming platform, Ubisoft+. It will also give Ubisoft the right to distribute Activision Blizzard games on other cloud gaming platforms.

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A band of 12 nations have issued a joint statement warning against the use of data scraping technologies to collect personal data from social media platforms and other online sites, which are required by local laws to safeguard their users' information.

They note that data scraping increasingly is used to gather and process vast amounts of individuals' personal information from the internet, raising significant privacy concerns as these technologies can be exploited for various purposes. These include monetization through reselling of the data to third-party websites, identity fraud, and threat intel gathering to facilitate malicious cyber attacks, according to the statement.

Also: Big tech is actually doing all this with your personal data. True or false?

The 12 nations include Australia, Canada, the UK, Hong Kong, and Switzerland, whose respective data privacy agencies were cited in the statement.

The Office of the Australian Information Commissioner (OAIC) said it had observed in recent years increased reports of mass data scraping from social media applications and other websites that host publicly accessible personal information. It pointed to a 2020 case involving US facial recognition platform Clearview AI, which the OAIC and the UK Information Commissioner's Office determined had breached Australia's privacy laws.

Under the country's Privacy Act 1988, organizations must take "reasonable steps" to protect personal data they hold from misuse, interference, loss, unauthorized access, and modification. These include actions as a result of unlawful data scraping, the OAIC said, adding that affected individuals must be notified when a data breach involving information collected through data scraping technologies is likely to result in serious harm to the individual.

Personal data that is publicly accessible is still subject to data protection and privacy regulations in most jurisdictions, the statement noted.

"Social media companies and the operators of websites that host publicly accessible personal data have obligations under data protection and privacy laws to protect personal information on their platforms from unlawful data scraping," it said. "Mass data scraping incidents that harvest personal information can constitute reportable data breaches in many jurisdictions."

Also: The best VPN services right now: Expert tested and reviewed

The 12 nations said they were expecting to gather feedback from companies that operate social media platforms, "over the coming weeks", on how they were complying or making plans to comply with the "expectations and principles" outlined in their joint statement.

The statement encompassed common global data protection practices that aim to help safeguard personal data against data scraping and mitigate the impact on personal privacy. While these are outlined as recommendations, the 12 nations stressed that many of the practices are "explicit statutory requirements" in specific jurisdictions.

They added that their joint statement had been sent directly to several of these websites, including Alphabet's YouTube, ByteDance's TikTok, Meta-owned platforms including Facebook and Threads, Sina's Weibo, X (formerly called Twitter), and Microsoft's LinkedIn.

The list of measures that the 12 nations expect these sites to take include "rate limiting" the number of visits per hour or day by a single account to other account profiles, and designating a specific team or roles within the organization to identify and implement controls in response to scraping activities.

Also: What is the dark web? Everything you need to know before you access it

Social media and websites that own personal data also should take steps to detect scrapers by identifying patterns in bot activities and take appropriate legal action, such as sending "cease and desist" letters and requiring the removal of scraped data, when illegal data scraping activities are identified.

These sites should implement "multi-layered technical and procedural controls to mitigate risks", the 12 nations said.

"Given the dynamic nature of data scraping threats, social media platforms and other websites should continuously monitor for, and respond with agility to, new security risks and threats from malicious or other unauthorized actors to their platform," they added. "Controls should be routinely stress-tested and updated to ensure they remain effective and keep pace with changing technologies."

The websites also should collect and analyze metrics on scraping incidents to identify areas of improvement in their security control approach, the nations said.

Security

The U.K. government will devote £100 million ($126 million USD) to fostering AI hardware development and shoring up possible computer chip shortages, according to a report from The Telegraph. The public sector organizations UK Research and Innovation and the Department for Science, Innovation and Technology are leading this effort.

Semiconductor chips have been in high demand and in limited supply because of the COVID-19 pandemic, stockpiling and other factors. In this economic climate, countries are trying to position themselves as stable havens for chipmakers to shore up supply against another shortage in the possible AI-powered future.

The U.K. is looking for semiconductor chips from these companies because they can be used to power generative AI models.

Jump to:

• How will the U.K.’s AI chip investment be used?
• Why is the UK government investing in AI?
• What the U.K.’s investment in AI means for businesses
• U.K. to host AI summit

How will the U.K.’s AI chip investment be used?

The £100 million allotment under Prime Minister Rishi Sunak will be used for chips suited for generative AI models, according to the Telegraph. In particular, the allotment asks for 5,000 GPUs from NVIDIA. The goal is to create a nationally-funded AI resource similar to the National Artificial Intelligence Research Resource Task Force in the U.S.

The U.K. also plans to put £900 million toward developing compute capacity, including an exascale supercomputer.

In March, the U.K. government pledged £3.5 billion to tech and innovation broadly, including about £1 billion of government funding for supercomputing and AI.

Why is the UK government investing in AI?

The £100 million investment is part of the global competition to be at the forefront of innovation in the relatively new AI sector. The U.K., which produces 0.5% of global semiconductor sales, is scrambling to compete with the European Union, U.S. and China, a U.K. government insider told The Guardian.

SEE: Most companies using generative AI task it with code development, content creation and analytics. (TechRepublic)

The U.S. invested $52 billion into its semiconductor industry with the CHIPS Act, which was signed into law on Tuesday, August 9, 2023. The European Union offered €43 billion ($46 billion USD) in subsidies with its European Chips Act, which was adopted on July 25, 2023.

The EU documentation points out that semiconductor chips have been at a premium and difficult to find for the last year. The acquisition of semiconductors depends on a small number of companies that produce them. This limited availability leads to competition between businesses and the countries in which those organizations reside.

Plus, the U.S. and China continue to compete to dominate the semiconductor industry, with the Biden administration restricting some U.S. investment in Chinese semiconductors, and China declaring U.S.-based manufacturer Micron‘s chips a security risk.

While the U.K. tries to establish itself as a home for the AI sector, it is contending with ongoing competition for the GPU chips — a category of one type of chip that typically falls under semiconductor manufacturing — that underlie heavy-duty generative AI models.

Today, the AI industry contributes £3.7 billion to the U.K. economy and employs 50,000 people.

What does the U.K.’s investment in AI mean for global businesses?

Aside from plans to secure hardware from NVIDIA, AMD and Intel, how the U.K.’s mix of AI investments and regulations will impact business depends a lot on whether your organization is an enterprise, a startup or something in between. AI regulation is a hot topic in the US and the U.K.

SEE: The Ada Lovelace Institute recently asked the U.K. government to firm up AI regulation proposals (TechRepublic)

Salesforce has committed to doing business in the U.K., with a $4 billion investment over the next five years announced in June 2023 and a stated interest in regulation that encourages, not stifles, innovation.

“A clear pro-innovation regulatory framework that compels safe and responsible use of AI is vital, and Salesforce is fully focused on bringing secure, trusted, enterprise ready generative AI to UK businesses,” said Zahra Bahrololoumi, chief executive officer of Salesforce UKI, in a press release.

“The U.K. clearly wants to position itself as more pro-innovation than the EU when it comes to technology, and especially AI,” said Andrew Gamino-Cheong, co-founder and chief technology officer of responsible AI governance platform Trustible, in an email to TechRepublic. “The EU’s AI Act doesn’t provide a lot of ‘carrot’ for good AI, mostly a ‘stick.'”

“A lot of the U.S. AI space is focusing on the U.S. market itself, and so there’s a huge opportunity for other non-U.S. AI players to emerge and cater towards the broader global economy,” Gamino-Cheong said. “The Chinese AI regulations are incompatible with the standards most other countries have, and so the non-U.S. and EU markets for AI are relatively underserved, and the U.K.’s deep connections to the international finance world can help it become an AI powerhouse serving those markets.”

U.K. to host AI summit

More information about the UK’s investment in AI innovation is expected to be available when the U.K. holds an AI Safety Summit this fall, likely in November, to try to hash out standards for safe use of artificial intelligence, particularly frontier solutions, meaning future-looking machine learning models. As of August 15, a formal date for the summit had not been set, several embassy officials told Politico.

“As AI rapidly evolves, we need a global approach that seizes the opportunities that AI poses while grasping the challenges and minimizing the risks,” said Foreign Secretary James Cleverly in a press release about the summit.

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Microsoft unveiled its Launcher application in 2017 to enable users to bring the Microsoft interface to their Android phones' home screen experience. Now, Launcher is getting an update that will incorporate generative AI.

Also: AI's multi-view wave is coming, and it will be powerful

As first spotted by Windows Central, Microsoft Launcher's latest beta build integrates Bing Chat into Launcher's search bar.

This means Launcher users on Android will no longer have to download and open the Bing app to start a conversation with Bing. Instead, all the users need to do is swipe down to access the Launcher's search functionality, where a Bing Chat icon will appear.

Once you tap the Bing Chat icon, you're taken to the Bing Chat interface on the website or the app.

This feature is especially convenient if you use the image search feature. If you want to identify something, such as a flower you saw on your walk, you can quickly open the Bing Chat search interface and upload the image there.

Also: How AI can improve cybersecurity by harnessing diversity

According to the report, the feature will also roll out to Surface Duo devices.

If you don't want to wait until it rolls out to you, you can sign up for Lancher's latest beta version. Microsoft does warn that "testing versions may be unstable" and that "Certain data on your use of the app will be collected and shared with the developer to help improve the app."

Artificial Intelligence