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Microsoft 365 Copilot Chat Agents Enter

Microsoft’s Office 365 Apps Get an AI Boost with Copilot Chat

Microsoft’s Office 365 apps have been the cornerstone for many working professionals’ day-to-day workflows for years. As a result, when the company developed its AI assistant, Copilot, it was only natural to infuse it across the 365 apps.

New Features in Microsoft 365 Copilot Chat

On Wednesday, Microsoft launched Microsoft 365 Copilot Chat, which builds on the traditional free Microsoft 365 Copilot chat experience. This new feature introduces pay-as-you-go agents that can automate repetitive tasks.

Agents: AI Assistants for Repetitive Tasks

With Microsoft 365 Copilot Chat, commercial customers can create, discover, and pin agents. Agents are AI assistants that can carry out repetitive tasks for you with minimal or no instruction. You can program them using natural language in Copilot Agent Builder and Copilot Studio, both accessible right in Copilot Chat.

Use Cases for Agents

Business use cases for agents could include a customer service representative using a CRM agent to provide them with account details before a meeting, or a field service agent accessing step-by-step instructions stored in SharePoint, according to Microsoft.

Additional Cost for Using Agents

Using agents does come at an additional cost, priced on a metered basis. The costs are determined by the sum of messages used by your organization, with message usage varying depending on the agent’s complexity and use of specific features, according to Microsoft. IT admins stay in control, with the ability to create organization-wide agents and manage agent deployment.

Conclusion

Microsoft 365 Copilot Chat is an exciting development in the world of AI assistants. With the introduction of pay-as-you-go agents, businesses can automate repetitive tasks and streamline their workflows. This feature is poised to become one of the most prominent AI trends in 2025, as companies continue to explore the possibilities of AI in the workplace.

Frequently Asked Questions

Q: What is Microsoft 365 Copilot Chat?

A: Microsoft 365 Copilot Chat is a new feature that builds on the traditional free Microsoft 365 Copilot chat experience, introducing pay-as-you-go agents that can automate repetitive tasks.

Q: What are agents in Microsoft 365 Copilot Chat?

A: Agents are AI assistants that can carry out repetitive tasks for you with minimal or no instruction. You can program them using natural language in Copilot Agent Builder and Copilot Studio.

Q: How much does it cost to use agents?

A: Using agents comes at an additional cost, priced on a metered basis. The costs are determined by the sum of messages used by your organization, with message usage varying depending on the agent’s complexity and use of specific features.

Q: How do I get started with Microsoft 365 Copilot Chat?

A: To get started, customers can visit the Copilot Chat website, where they should see the new “Create agent” option on the right-hand tab.

MiniMax releases new models competitive with industry’s best

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Chinese firms continue to release AI models that rival the capabilities of systems developed by OpenAI and other U.S.-based AI companies.

MiniMax Debuts New AI Models

This week, MiniMax, an Alibaba- and Tencent-backed startup that has raised around $850 million in venture capital and is valued at more than $2.5 billion, debuted three new models: MiniMax-Text-01, MiniMax-VL-01, and T2A-01-HD. MiniMax-Text-01 is a text-only model, while MiniMax-VL-01 can understand both images and text. T2A-01-HD, meanwhile, generates audio — specifically speech.

Performance Compared to Other Models

MiniMax claims that MiniMax-Text-01, which is 456 billion parameters in size, performs better than models such as Google’s recently unveiled Gemini 2.0 Flash on benchmarks like MATH and SimpleQA, which measure the ability of a model to answer math problems and fact-based questions. Parameters roughly correspond to a model’s problem-solving skills, and models with more parameters generally perform better than those with fewer parameters.

As for MiniMax-VL-01, MiniMax says that it rivals Anthropic’s Claude 3.5 Sonnet on evaluations that require multimodal understanding, like ChartQA, which tasks models with answering graph- and diagram-related queries (e.g., “What is the peak value of the orange line in this graph?”). Granted, MiniMax-VL-01 doesn’t quite best Gemini 2.0 Flash on many of these tests. OpenAI’s GPT-4o and Meta’s Llama 3.1 beat it on several as well.

Features and Availability

Of note, MiniMax-Text-01 has an extremely large context window. A model’s context, or context window, refers to input (e.g., text) that a model considers before generating output (additional text). With a context window of 4 million tokens, MiniMax-Text-01 can analyze around 3 million words in one go — or just over five copies of “War and Peace.”

For context (no pun intended), MiniMax-Text-01’s context window is roughly 31 times the size of GPT-4o’s and Llama 3.1’s.

The last of MiniMax’s models released this week, T2A-01-HD, is an audio generator optimized for speech. T2A-01-HD can generate a synthetic voice with adjustable cadence, tone, and tenor in around 17 different languages, including English and Chinese, and clone a voice from just 10 seconds of an audio recording.

MiniMax didn’t publish benchmark results comparing T2A-01-HD to other audio-generating models. But to this reporter’s ear, T2A-01-HD’s outputs sound on par with audio models from Meta and startups like PlayAI.

License and Availability

MiniMax’s new models can be downloaded from GitHub and the AI dev platform Hugging Face. However, with the exception of T2A-01-HD, which is exclusively available through MiniMax’s API and Hailuo AI platform, MiniMax’s other models are subject to certain restrictions. MiniMax-Text-01 and MiniMax-VL-01 aren’t truly open source in the sense that MiniMax hasn’t released the components (e.g., training data) needed to re-create them from scratch. Moreover, they’re under MiniMax’s restrictive license, which prohibits developers from using the models to improve rival AI models and requires that platforms with more than 100 million monthly active users request a special license from MiniMax.

Controversy Surrounds MiniMax’s Products

Some of MiniMax’s products have become the subject of minor controversy.

Talkie, which was pulled from Apple’s App Store in December for unspecified “technical” reasons, features AI avatars of public figures, including Donald Trump, Taylor Swift, Elon Musk, and LeBron James, none of whom appear to have consented to being featured in the app.

In December, Broadcast magazine reported that MiniMax’s video generators can reproduce the logos of British television channels, suggesting that MiniMax’s models were trained on content from those channels. And MiniMax is reportedly being sued by iQiyi, a Chinese video streaming service that alleges MiniMax illicitly trained on iQIYI’s copyrighted recordings.

Regulatory Developments

MiniMax’s new models arrive days after the outgoing Biden Administration proposed harsher export rules and restrictions on AI technologies for Chinese ventures. Companies in China were already prevented from buying advanced AI chips, but if the new rules go into effect as written, companies will be faced with stricter caps on both the semiconductor tech and models needed to bootstrap sophisticated AI systems.

On Wednesday, the Biden Administration announced additional measures focused on keeping sophisticated chips out of China. Chip foundries and packaging companies that want to export certain chips will be subjected to broader license requirements unless they exercise greater scrutiny and due diligence to prevent their products from reaching Chinese clients.

Conclusion

MiniMax’s release of three new AI models showcases the rapid advancement of AI technology in China and the increasing rivalry between Chinese firms and their US-based counterparts. While the performance of MiniMax’s models is impressive, their availability is limited by restrictive licensing agreements and raises questions about the transparency and ownership of the underlying technology.

FAQs

Q: What is MiniMax’s valuation?
A: MiniMax is valued at more than $2.5 billion.

Q: What is the size of MiniMax-Text-01?
A: MiniMax-Text-01 is 456 billion parameters in size.

Q: How large is the context window of MiniMax-Text-01?
A: The context window of MiniMax-Text-01 is 4 million tokens, allowing it to analyze around 3 million words in one go.

Q: What is T2A-01-HD?
A: T2A-01-HD is an audio generator optimized for speech, capable of generating a synthetic voice with adjustable cadence, tone, and tenor in 17 different languages.

Q: Are MiniMax’s models available for download?
A: MiniMax’s new models can be downloaded from GitHub and the AI dev platform Hugging Face, with the exception of T2A-01-HD, which is exclusively available through MiniMax’s API and Hailuo AI platform.

Mistral Signs AFP Deal for Fact-Based Chatbot

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French AI Start-up Strikes Deal with Agence France-Presse to Integrate News Articles into Chatbot

French artificial intelligence start-up Mistral has struck a multimillion-euro deal with Agence France-Presse (AFP) to incorporate thousands of the newswire’s articles into its chatbot, pitching the tie-up as a European bulwark against attacks on fact-checking from its Silicon Valley rivals.

Partnership to Ensure Well-Grounded Information

The deal, announced on Thursday, will feed more than 2,000 AFP news articles in six languages every day into Mistral’s chatbot, Le Chat, allowing users to answer questions and help draft documents. "It’s important to have such agreements to have well-grounded information on validated content," said Arthur Mensch, Mistral’s co-founder and chief executive.

Countering Silicon Valley Rivals

The partnership comes as Meta and Elon Musk’s X have pulled back on content moderation and declared the primacy of "free speech", in the run-up to incoming US President Donald Trump’s inauguration. "What it tells us is that Europe must unite to defend its thriving technological sector," Mensch said about recent moves by Silicon Valley rivals. "Free speech is being weaponized against Europe to a great extent and there is this offensive by Big Tech on European regulation."

Deal Represents Opportunity for AFP to Make Up Revenue

The deal with Mistral also represents an opportunity for AFP to make up revenue that will be lost as its fact-checking contract with Meta winds down. The US social media group said last week that it planned to shift to community-based fact-checking in the US. AFP has 150 journalists working for Meta on fact-checking, according to Fries.

Commercial Terms of the Deal

Commercial terms of the deal, which runs over multiple years, were not disclosed. But unlike similar agreements struck between US-based OpenAI and other media groups, Fries said the deal was "not a one-off settlement" for data on which large language models are trained.

Conclusion

In a rapidly changing media landscape, the partnership between Mistral and Agence France-Presse represents a significant step forward in the fight against misinformation and disinformation. By integrating AFP’s news articles into its chatbot, Mistral is ensuring that users have access to well-grounded information and well-validated content.

FAQs

Q: What is the deal between Mistral and Agence France-Presse?
A: The deal is a multimillion-euro agreement to incorporate thousands of AFP’s news articles into Mistral’s chatbot, Le Chat.

Q: What is the purpose of the deal?
A: The deal aims to ensure well-grounded information on validated content and counter the attacks on fact-checking from Silicon Valley rivals.

Q: How many articles will be integrated into the chatbot?
A: More than 2,000 AFP news articles in six languages will be integrated into the chatbot every day.

GPU Memory Essentials for AI Performance

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The Parameter-Precision Balance in AI Models

To calculate the GPU memory size needed, it’s essential to understand two key concepts: parameters and precision.

Parameters

Parameters are the learned values within a model that determine its behavior. Think of parameters as the knowledge of an AI model. They’re like the countless tiny adjustments a model makes as it learns. For example, in a language model, parameters help it understand the relationships between words and concepts. The more parameters a model has, the more complex patterns it can potentially understand, but also the more memory it requires.

Precision

Precision refers to the level of detail retained when storing these parameters in memory. It’s like choosing between a regular ruler and a super-precise scientific instrument. Higher precision (32-bit or FP32, for example) is like using a caliper or a micrometer. It gives more accurate measurements, but takes up more space when writing down many more digits. Lower precision (16-bit or FP16, for example) is like using a simple ruler. It saves space but might lose some tiny details.

The Total Memory Needed

The total memory needed for a model depends both on how many parameters it has and how precisely each parameter is stored. Choosing the right balance between the number of parameters and precision is crucial, as more parameters can make a model smarter but also require more memory. On the other hand, lower precision saves memory but might slightly reduce the model’s capabilities.

GPU Memory for AI Models

To estimate the GPU memory required, first find the number of parameters. One way is to visit the NVIDIA NGC catalog and check the model name or the model card. Many models include parameter counts in their names; for example, GPT-3 175B indicates 175 billion parameters. The NGC catalog also provides detailed information about models, including parameter counts in the Model Architecture or Specifications section.

Precision of a Pretrained Model

To determine the precision of a pretrained model, you can examine the model card for specific information about the data format used. FP32 (32-bit floating-point) is often preferred for training or when maximum accuracy is crucial. It offers the highest level of numerical precision but requires more memory and computational resources. FP16 (16-bit floating-point) can provide a good balance of performance and accuracy, especially on NVIDIA RTX GPUs with Tensor Cores.

Quantization Techniques

For developers looking to run larger models on GPUs with limited memory, quantization techniques can be a game-changer. Quantization reduces the precision of the model’s parameters, significantly decreasing memory requirements while maintaining most of the model’s accuracy. NVIDIA TensorRT-LLM offers advanced quantization methods that can compress models to 8-bit or even 4-bit precision, enabling you to run larger models with less GPU memory.

Conclusion

Running AI models locally on powerful workstations is becoming increasingly important. To get started, you can use NVIDIA AI Workbench to bring AI capabilities like NVIDIA NIM microservices right to your desktop, unlocking new possibilities in gaming, content creation, and beyond.

Frequently Asked Questions

Q: How do I estimate the GPU memory required for an AI model?
A: You can estimate the GPU memory required by finding the number of parameters and the precision of the model.

Q: What is precision in AI models?
A: Precision refers to the level of detail retained when storing parameters in memory.

Q: How do I reduce memory requirements for large AI models?
A: You can reduce memory requirements by using quantization techniques, which reduce the precision of the model’s parameters.

Q: What are NVIDIA TensorRT-LLM advanced quantization methods?
A: NVIDIA TensorRT-LLM offers advanced quantization methods that can compress models to 8-bit or even 4-bit precision, enabling you to run larger models with less GPU memory.

Q: How can I get started with NVIDIA AI Workbench?
A: You can get started with NVIDIA AI Workbench by registering to join PNY and NVIDIA for the webinar, Maximizing AI Training with NVIDIA AI Platform and Accelerated Solutions.

Beating China in AI Brings Its Own Risks

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The New AI Export Restrictions and the Global AI Landscape

The Latest Move in the US-China AI Rivalry

The Biden administration has introduced new export restrictions aimed at controlling the progress of AI globally and preventing the most advanced AI from falling into China’s hands. This move is the latest in a series of measures taken by the Trump and Biden administrations to keep Chinese AI in check.

Expert Insights on the New Rule

To gain a deeper understanding of the new rule and its implications, I spoke with Paul Triolo, a partner at DGA Group, and Alvin Graylin, an entrepreneur who previously ran China operations for the Taiwanese electronics firm HPC. Here’s what they had to say:

Uncertainty and Complexity

The new rule focuses on clusters of high-performance computing and puts controls on proprietary model weights for the most advanced "frontier" models. However, the unclear compliance conditions and performance levels inject uncertainty into the long-term plans of both medium and major US and Western hyperscalers.

The Impact on the AI Industry

For hyperscalers like Google, Microsoft, AWS, and Oracle, the rule introduces critical issues, including slowed or more complex international expansion, new compliance and legal costs, impact on global R&D, and uncertain enforcement requirements.

The Effectiveness of Previous Measures

US export controls have slowed China, but they have also unified the will and efforts of the Chinese government to become more self-reliant, investing tens of billions in helping local players catch up technologically or scale capacity in core areas, resulting in significant changes within the semiconductor industry and its ability to support advanced hardware for developing frontier AI models.

The "Beat China" Rhetoric

The growing link between conservative venture capitalists, mostly located in Silicon Valley, and technology companies whose business models depend on hyping the China threat, is a troubling combination that conflates the China threat, personal gain, and pushback against regulation of advanced AI. This portrayal of US-China competition around AI as a zero-sum game is particularly dangerous.

Conclusion

The new AI export restrictions are another move in the ongoing efforts to control the global AI landscape and prevent advanced AI from falling into Chinese hands. While the rule aims to curb China’s progress, it also injects uncertainty into the long-term plans of major players in the AI industry. The "beat China" rhetoric, fueled by conservative venture capitalists and technology companies, is a concerning trend that ignores the complexities of the global AI landscape and the need for a more nuanced approach to AI development and regulation.

FAQs

Q: What does the new AI export rule aim to achieve?
A: The new rule aims to control the progress of AI globally and prevent the most advanced AI from falling into China’s hands.

Q: How will the rule affect the AI industry?
A: The rule will introduce uncertainty and complexity, leading to slowed or more complex international expansion, new compliance and legal costs, impact on global R&D, and uncertain enforcement requirements for hyperscalers like Google, Microsoft, AWS, and Oracle.

Q: How have previous measures affected the AI industry in China?
A: US export controls have slowed China, but they have also unified the will and efforts of the Chinese government to become more self-reliant, investing tens of billions in helping local players catch up technologically or scale capacity in core areas.

Q: Why is the "beat China" rhetoric concerning?
A: The portrayal of US-China competition around AI as a zero-sum game is particularly dangerous, as it ignores the complexities of the global AI landscape and the need for a more nuanced approach to AI development and regulation.

Gmail’s New Button Makes Replying to Emails Easy on Android

Google is making it easier to use Gemini, the AI-powered feature in Gmail, by adding a simple "Insert" button to the Android version of the app. This button allows users to easily insert AI-written messages into the reply window, making it a more seamless experience.

The new button is located on the bottom row of the screen, next to the thumbs up and thumbs down buttons, and below other tools like formalize, elaborate, and shorten. When clicked, Gemini sends the current version of the AI-written message into the reply window, ready to be edited and sent.

The feature was first spotted in December, but appears to be rolling out to a wider audience now. If you don’t see it yet, you should soon.

Gemini is a powerful tool that can do more than generate messages. It can also:

  • Find information from Google Drive files
  • Search for specific types of emails (e.g. "Show unread emails only from the past 5 days" or "Emails from Chris sent last week")
  • Provide information about Google Calendar events
  • Summarize entire email threads
  • Create events in your Google Calendar

Gemini’s capabilities can greatly enhance your email experience, and the new "Insert" button makes it even easier to use.

FAQs:

Q: What is Gemini?
A: Gemini is an AI-powered feature in Gmail that can generate messages, summarize emails, and provide other information.

Q: What can Gemini do?
A: Gemini can generate messages, summarize entire email threads, provide information from Google Drive files, search for specific types of emails, provide information about Google Calendar events, and create events in your Google Calendar.

Q: How do I use the new "Insert" button?
A: You can find the new "Insert" button on the bottom row of the screen, next to the thumbs up and thumbs down buttons, and below other tools like formalize, elaborate, and shorten. Click the button to send the AI-written message into the reply window, where you can edit and send it.

10 FREE AI Productivity Apps Your Phone Needs Now

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AI Productivity Tools I Recommend

As a productivity enthusiast, I’m always on the lookout for tools that can help me stay organized and focused. In this article, I’ll share my top picks for AI-powered productivity tools that have made a significant impact on my workflow.

1. Grammarly

Grammarly is a writing tool that uses AI to help you improve your writing skills. With its advanced grammar and spell check, you can ensure that your writing is error-free and polished. Grammarly also offers suggestions for improving your writing style, tone, and clarity.

Features:

* Advanced grammar and spell check
* Writing style suggestions
* Tone and clarity analysis
* Integration with popular writing platforms

2. Trello

Trello is a project management tool that uses AI to help you stay organized and focused. With its Kanban-style boards, you can visualize your tasks and projects, and prioritize them accordingly. Trello also offers integrations with other tools and services, making it a versatile productivity solution.

Features:

* Kanban-style boards
* Task prioritization
* Integration with other tools and services
* Mobile app for on-the-go access

3. Evernote

Evernote is a note-taking app that uses AI to help you organize and prioritize your notes. With its advanced search functionality, you can quickly find the information you need. Evernote also offers integrations with other tools and services, making it a powerful productivity solution.

Features:

* Advanced search functionality
* Note organization and prioritization
* Integration with other tools and services
* Mobile app for on-the-go access

4. RescueTime

RescueTime is a time management tool that uses AI to help you understand how you spend your time. With its detailed reports and analytics, you can identify areas where you can improve your productivity. RescueTime also offers alerts and notifications to help you stay on track.

Features:

* Time tracking and analytics
* Detailed reports and insights
* Alerts and notifications
* Integration with popular productivity tools

5. Focus@Will

Focus@Will is a music service that uses AI to help you stay focused and productive. With its scientifically-designed music tracks, you can improve your concentration and reduce distractions. Focus@Will also offers a mobile app for on-the-go access.

Features:

* Scientifically-designed music tracks
* Improved concentration and focus
* Mobile app for on-the-go access
* Integration with popular productivity tools

Conclusion

These AI-powered productivity tools have made a significant impact on my workflow, and I’m confident they can do the same for you. Whether you’re looking to improve your writing skills, stay organized, or boost your productivity, there’s an AI tool on this list that can help.

FAQs

Q: What is AI-powered productivity?

A: AI-powered productivity refers to the use of artificial intelligence to improve your workflow and increase your productivity. These tools use machine learning algorithms to analyze your behavior and provide personalized recommendations and insights.

Q: How do I get started with AI-powered productivity tools?

A: Getting started with AI-powered productivity tools is easy. Simply sign up for the tool, and start using it. Most tools offer a free trial or a basic plan, so you can try them out before committing to a paid plan.

Q: Are AI-powered productivity tools secure?

A: Yes, most AI-powered productivity tools are secure. They use encryption and other security measures to protect your data and ensure that it’s only accessible to you.

Q: Can I use AI-powered productivity tools on my mobile device?

A: Yes, most AI-powered productivity tools offer mobile apps or mobile-friendly websites, so you can access them on-the-go.

More teens report using ChatGPT for schoolwork, despite its faults

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Younger Gen Zers Embracing ChatGPT for Schoolwork, But Awareness of Pitfalls is Lacking

A new survey by the Pew Research Center has found that younger Gen Zers are increasingly using OpenAI’s AI-powered chatbot, ChatGPT, for schoolwork. However, it’s unclear whether they are fully aware of the technology’s limitations and potential pitfalls.

Increased Adoption

The survey, which polled around 1,400 U.S.-based teens aged 13-17, found that 26% of respondents had used ChatGPT for homework or other school-related assignments. This is double the number reported two years ago.

Acceptability of ChatGPT Use

The survey also asked teens about their attitudes towards using ChatGPT for different types of schoolwork. Just over half (54%) of respondents said it was acceptable to use ChatGPT for researching new subjects, while 29% said it was acceptable for math problems, and 18% said it was acceptable for writing essays.

Pitfalls of ChatGPT

However, considering the limitations of ChatGPT, the results are potentially cause for alarm. ChatGPT is not always accurate, and it can struggle with complex tasks such as math problems. A recent study found that ChatGPT was only able to answer questions slightly more accurately than a person randomly guessing.

Furthermore, ChatGPT has been shown to be weakest in areas relevant to the demographics of teens who report using it the most in school. For example, a study found that ChatGPT struggled with questions about social mobility and the geopolitics of Sub-Saharan Africa, which may be particularly important for Black and Hispanic teens who are more likely to use ChatGPT for schoolwork.

Research on ChatGPT’s Impact

Research on the impact of ChatGPT on education is mixed. Some studies have found that students who use ChatGPT tend to perform worse on tests, while others have found that it can help students find research materials more easily but may not improve their ability to synthesize information.

Teacher Perspectives

A separate poll by Pew found that a quarter of public K-12 teachers believe that using AI tools like ChatGPT in education does more harm than good. Additionally, a survey by the Rand Corporation and the Center on Reinventing Public Education found that only 18% of K-12 educators use AI in their classrooms.

Conclusion

While ChatGPT may be a useful tool for some students, it is important for educators and parents to be aware of its limitations and potential pitfalls. As the technology continues to evolve, it is crucial that we prioritize critical thinking and media literacy skills to ensure that students are able to effectively use AI tools like ChatGPT.

FAQs

Q: What percentage of teens have used ChatGPT for schoolwork?

A: 26% of teens aged 13-17 have used ChatGPT for homework or other school-related assignments.

Q: Is ChatGPT accurate?

A: ChatGPT is not always accurate and can struggle with complex tasks such as math problems. A recent study found that ChatGPT was only able to answer questions slightly more accurately than a person randomly guessing.

Q: Is ChatGPT acceptable for all types of schoolwork?

A: The survey found that 54% of teens believe it is acceptable to use ChatGPT for researching new subjects, while 29% said it was acceptable for math problems, and 18% said it was acceptable for writing essays.

Q: What do teachers think about using ChatGPT in education?

A: A quarter of public K-12 teachers believe that using AI tools like ChatGPT in education does more harm than good, while only 18% of K-12 educators use AI in their classrooms.

Creator Content Boom

The race for AI video training has taken an unexpected turn. Major tech companies are now paying content creators thousands of dollars for their unused footage, marking a significant shift in how artificial intelligence companies acquire training data.

AI Companies Seek Exclusive Content

In a revealing report from Bloomberg, tech giants including Google, OpenAI, and Moonvalley are actively seeking exclusive, unpublished video content from YouTubers and digital content creators to train AI algorithms. The move comes as companies compete to develop increasingly sophisticated AI video generators.

The Economics of the New Market

According to Bloomberg’s findings, AI companies are willing to pay between $1 and $4 per minute for video footage, with rates varying based on quality and uniqueness. Premium content, such as 4K video footage, drone captures, and 3D animations, commands higher prices, while standard unused content from platforms like YouTube, Instagram, or TikTok typically sells for $1-2 per minute.

Specialized Intermediaries Emerge

The development of the market has given rise to specialized intermediaries. Companies like Troveo AI and Calliope Networks have emerged as third-party licensing facilitators, managing rights for thousands of hours of video footage owned by creators. These companies handle negotiations with content creators and bundle the content for AI companies, streamlining the process for both parties.

Benefits for Content Creators

For content creators, this presents an opportunity to monetize footage that would otherwise remain unused. Many creators accumulate hundreds of hours of footage annually while producing content for various platforms, but only a fraction of their material makes it into a final, published video.

Safeguards and Protections

The deals come with safeguards. Most agreements include specific terms preventing AI companies from creating digital replicas of content creators’ work or mimicking exact scenes from their channels. These protections ensure that creators’ brands and reputations remain intact while participating in AI video training.

Conclusion

The trend of AI companies acquiring exclusive content from content creators marks a significant shift in the relationship between the two parties. Rather than having their public content scraped without compensation, creators now have the opportunity to participate actively in and benefit from AI development.

FAQs

Q: What is the purpose of AI companies acquiring exclusive content from content creators?
A: AI companies are seeking to develop increasingly sophisticated AI video generators, and acquiring exclusive content helps them achieve this goal.

Q: How much do AI companies pay for video footage?
A: AI companies pay between $1 and $4 per minute for video footage, with rates varying based on quality and uniqueness.

Q: What are specialized intermediaries, and what do they do?
A: Specialized intermediaries, such as Troveo AI and Calliope Networks, manage rights for thousands of hours of video footage owned by creators and handle negotiations with content creators and bundle the content for AI companies.

Q: What safeguards are in place to protect content creators’ brands and reputations?
A: Most agreements include specific terms preventing AI companies from creating digital replicas of content creators’ work or mimicking exact scenes from their channels.

Embracing AI-Driven Security for the Modern Enterprise

Securing Enterprises in the AI Era: A New Normal

As AI becomes increasingly integral to business operations, new safety concerns and security threats emerge at an unprecedented pace—outstripping the capabilities of traditional cybersecurity solutions. The stakes are high, with potentially significant repercussions. According to Cisco’s 2024 AI Readiness Index, only 29% of surveyed organisations feel fully equipped to detect and prevent unauthorised tampering with AI technologies.

Continuous Model Validation

DJ Sampath, Head of AI Software & Platform at Cisco, emphasizes the importance of continuous model validation. "When we talk about model validation, it is not just a one-time thing, right? You’re doing the model validation on a continuous basis. As you see changes happen to the model – if you’re doing any type of fine-tuning, or you discover new attacks that are starting to show up that you need the models to learn from – we’re constantly learning all of that information and revalidating the model to see how these models are behaving under these new attacks that we’ve discovered."

Evolution Brings New Complexities

Frank Dickson, Group VP for Security & Trust at IDC, highlights the evolution of cybersecurity over time and what advancements in AI mean for the industry. "The first macro trend was that we moved from on-premise to the cloud and that introduced this whole host of new problem statements that we had to address. And then as applications move from monolithic to microservices, we saw this whole host of new problem sets."

Adjusting to the New Normal

Jeetu Patel, Executive VP and Chief Product Officer at Cisco, notes that major advancements in a short period of time always seem revolutionary but quickly feel normal. "Waymo is, you know, self-driving cars from Google. You get in, and there’s no one sitting in the car, and it takes you from point A to point B. It feels mind-bendingly amazing, like we are living in the future. The second time, you kind of get used to it. The third time, you start complaining about the seats."

Conclusion

As AI and large language models continue to evolve, it is crucial for enterprises to stay ahead of the curve. Cisco’s AI Defense is a self-optimising solution that uses proprietary machine learning algorithms to identify evolving AI safety and security concerns, informed by threat intelligence from Cisco Talos.

Frequently Asked Questions

Q: What is the current state of AI security in enterprises?
A: The current state of AI security in enterprises is a growing concern, with new threats and vulnerabilities emerging at an unprecedented pace.

Q: What is Cisco’s approach to AI security?
A: Cisco’s approach to AI security is to provide a self-optimising solution that uses proprietary machine learning algorithms to identify evolving AI safety and security concerns, informed by threat intelligence from Cisco Talos.

Q: How can enterprises stay ahead of the curve in AI security?
A: Enterprises can stay ahead of the curve in AI security by implementing solutions like Cisco’s AI Defense, which provides continuous model validation and threat intelligence to help prevent unauthorised tampering with AI technologies.

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