The Dangers of Artificial Intelligence and How to Mitigate Them

– AI-powered weapons, job loss, privacy violations, and more

Artificial intelligence (AI) has the potential to revolutionize many industries and make our lives easier in countless ways. However, as with any powerful technology, there are also dangers associated with AI that must be acknowledged and addressed. In this article, we will explore some of the most significant risks of AI, including its use in malicious ways, in warfare, job loss, privacy violations, and more.

The Use of AI in Malicious Ways

One of the biggest concerns surrounding AI is the potential for it to be used in malicious ways. With the ability to process large amounts of data quickly and make decisions based on that data, AI could be used to automate hacking and other cyberattacks, making them more difficult to detect and defend against. This could lead to a significant increase in cybercrime and other types of malicious activity.

The Use of AI in Warfare

Another concern is the potential for AI to be used in warfare. Autonomous weapons, which are capable of making their own decisions about when to use deadly force, are already being developed by several countries. This could lead to a future in which AI-powered weapons are used on the battlefield, potentially leading to even more destruction and loss of life.

Job Loss Due to AI

Another potential danger of AI is the loss of jobs. As AI becomes more advanced and capable of performing a wider range of tasks, it is likely to take over many jobs currently done by humans. This could lead to widespread unemployment and social upheaval, as people struggle to find new work in the face of increasing automation.

Privacy Violations by AI

In addition to these concerns, there is also the potential for AI to be used to violate people’s privacy. With the ability to collect and analyze vast amounts of personal data, AI could be used to track people’s movements, monitor their online activity, and even manipulate their behavior. This could lead to a future in which people’s privacy is routinely violated by AI-powered systems.

Solutions to the Dangers of AI

One possible solution to these problems is the development of ethical guidelines for the use of AI. These guidelines could be used to ensure that AI is developed and used in a responsible way, taking into account the potential risks and ensuring that the benefits of AI outweigh the potential drawbacks.

Another potential solution is the development of AI that is designed to be more transparent and accountable. By making AI systems more transparent, it would be easier to understand how they are making decisions and to identify any potential problems or biases. This could help to reduce the risks associated with AI and make it more trustworthy.

In conclusion, while AI has the potential to be a powerful force for good, it is important that we remain vigilant and take steps to mitigate the potential dangers of AI. By working together and taking a responsible approach to AI development and use, we can ensure that AI is a force for good, rather than a source of danger.

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FileBase: Decentralized Storage for the Future of Backup and Restore

In an era where blockchain technology is gaining more attention than ever before, it’s no surprise that innovative solutions are emerging to address various needs. One such solution that caught our eye is FileBase, a decentralized storage network that leverages blockchain technology to provide secure, scalable, and cost-effective object storage for backup and restore purposes. As a Veeam Backup & Replication user, the possibility of integrating FileBase into our backup infrastructure is an exciting prospect, offering numerous benefits over traditional storage solutions.

In this article, we’ll delve into FileBase’s features, pricing, and capabilities, as well as provide step-by-step instructions for configuring Blockchain-based storage fronted by Amazon S3 Compatible platforms using Veeam Backup & Replication v9.5 Update 4. We’ll also explore the potential benefits and challenges of adopting this technology and look into the future developments of FileBase.

FileBase Overview

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FileBase is a decentralized storage network that utilizes blockchain technology to provide secure, scalable, and cost-effective object storage. The platform operates on a de-centralized architecture, meaning there are no centralized nodes or servers to manage. Instead, FileBase relies on a network of distributed hosts, each storing a portion of the data. This design ensures that data is redundantly stored across many nodes, providing high availability and native redundancy.

FileBase features Sia as its backend BlockChain network, which allows for the creation of cryptographic service-level agreements (SLAs) that are stored on the Sia blockchain. Every object uploaded to FileBase is split into 30 pieces using Reed-Solomon erasure coding, ensuring that data is distributed across multiple hosts and providing a high level of redundancy.

Pricing and Capabilities

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FileBase offers a free tier of 5GB for all users, with subscriptions starting at $5.99 per month for 1TB of storage and 1TB of transfer. Storage costs $0.0059/GB, and outbound transfers cost $0.0059/GB. Ingress is always free.

FileBase’s capabilities extend beyond just object storage. The platform also offers features such as edge computing, data analytics, and machine learning. This makes it an ideal solution for backup and restore purposes, as well as other use cases that require large amounts of scalable storage.

Configuring Blockchain-Based Storage with Veeam Backup & Replication

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To integrate FileBase into your Veeam Backup & Replication infrastructure, follow these steps:

1. Create a new Object Storage Repository of type Amazon S3 Compatible in Veeam Backup Infrastructure.

2. Enter the following details:

* Region (not listed in the documentation, but can be found here)

+ Bucket Name (e.g., your-bucket-name)

+ Endpoint URL (e.g., https://your-bucket-name.filebase.com)

3. Add the bucket, create a folder, and save the new Object Storage Repository as per usual.

4. Configure a new SOBR with a Capacity Tier extent backed by FileBase Object Storage Repository.

5. Once a job is configured to use the SOBR, you can move or copy backup data into the Capacity Tier, which is sitting on a super-decentralized, distributed storage layer leveraging BlockChain!

below you can see data being copied up to FileBase as a result of the Backup Job completing and the offload task doing its thing.

Future Developments and Challenges

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FileBase is an innovative solution that addresses various needs in the backup and storage industry. As the technology continues to evolve, we can expect to see further developments and improvements. Some potential future developments could include:

1. Enhanced Compliance and Regulation Support: As compliance regulations become more prevalent, FileBase may need to adapt to accommodate these requirements.

2. Increased Scalability: As the platform grows, it will be essential to ensure that FileBase can scale accordingly to meet the demands of its user base.

3. Integration with Other Blockchain Solutions: The potential for integrating FileBase with other blockchain solutions, such as those focused on data privacy and security, could provide an even more comprehensive solution.

4. Improved User Interface: A user-friendly interface could make it easier for users to interact with the platform and manage their backup and storage needs.

Challenges that FileBase may face include:

1. Regulatory Compliance: As blockchain technology continues to mature, regulatory compliance will become increasingly important.

2. User Adoption: The decentralized nature of FileBase may be challenging for some users who are accustomed to more traditional storage solutions.

3. Scalability: Maintaining performance and scalability as the user base grows could present challenges.

Conclusion

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FileBase is an exciting solution that leverages blockchain technology to provide secure, scalable, and cost-effective object Storage for backup and restore purposes. With its decentralized architecture, native redundancy, and cryptographic SLAs, FileBase offers a compelling alternative to traditional storage solutions. As the platform continues to evolve and address various needs in the industry, we can expect to see continued growth and adoption of this innovative technology.

Donald Trump’s Paper Wealth Could Reach Over $1 Billion by End of Day Tuesday

Former President Donald Trump could potentially pocket over $1 billion in paper wealth by the end of the day on Tuesday, according to a Securities and Exchange Commission (SEC) filing last week. This is based on the performance of Trump Media & Technology Group (TMTG), the company behind Trump’s social media platform Truth Social, which went public on March 26.

The clock began ticking on a 30-day period on March 26, during which TMTG’s dollar volume-weighted average price (DVWAP) must be at least $12.50 for a minimum of 20 trading days. If this condition is met, Trump will earn 36 million earnout shares of TMTG, bringing his potential wealth to over $1 billion.

As of Friday’s closing price of $36.38 per share, the potential value of the earnout shares is $1.3 billion. Trump owned approximately 57.6% of the outstanding shares of TMTG when it debuted on the public markets, or 78.75 million shares. With a market capitalization of $4.97 billion at the end of last week, Trump Media closed out its first trading week with a high of $79.38 per share, giving the company a more than $8 billion market cap.

However, the stock began to nosedive over several weeks following disclosures of multi-million dollar losses from operations in 2023, the registered resale of substantially all of its outstanding securities, and the announcement of its own live TV streaming platform. As a result, Trump Media stock rebounded toward the end of last week and recovered more than $1 billion in market value.

It’s important to note that this potential wealth is purely paper wealth, as the earnout shares are contingent on TMTG’s performance and are not yet in Trump’s possession. Additionally, the stock market can be volatile, and the value of Trump’s stake in TMTG could fluctuate based on various factors such as economic conditions, industry trends, and investor sentiment.

Overall, the potential wealth that Donald Trump could pocket by the end of the day on Tuesday is a result of the performance of Trump Media & Technology Group, and the company’s success in meeting certain financial milestones. While the stock market can be unpredictable, Trump’s stake in TMTG has already shown significant growth since its debut on the public markets.

FileBase: Decentralized Storage for the Future of Backup and Recovery

In the world of cloud storage, there is a growing trend towards decentralization, and FileBase is at the forefront of this movement. As a BlockChain-based object storage solution, FileBase offers a unique approach to storing data that not only provides redundancy and high availability but also leverages the power of BlockChain technology. With its recent seed round funding, FileBase is poised to revolutionize the backup and recovery industry.

Decentralized Storage for the Future

FileBase’s decentralized storage mechanism creates native redundancy and high availability, ensuring that data is safe and accessible even in the event of a host failure. By splitting files into 30 pieces using Reed-Solomon erasure coding, each piece is geographically distributed to Sia hosts all around the world. This means that if 20 out of 30 hosts go offline, a Sia client can still download the files.

BlockChain Technology for Cryptographic SLAs

FileBase uses BlockChain technology to create cryptographic service-level agreements (SLAs) that are stored on the Sia blockchain. This ensures that renters form file contracts with hosts, setting pricing, uptime commitments, and other aspects of their relationship. File contracts are a type of smart contract, providing a secure and transparent way to manage storage and retrieval of data.

Object Storage Repositories for Veeam Backup & Replication

With Veeam Backup & Replication v9.5 Update 4, Object Storage Support for the Scale Out Backup Repository has been added. This means that FileBase’s Amazon S3 Compatible platform can now be used as a backup repository for Veeam backups. To configure BlockChain-based storage fronted by Amazon S3 Compatible, simply create a new Bucket in the FileBase console, select your backend (SIA or Storg), and obtain your S3 API Access and Secret Key details. Then, in Veeam Backup & Replication, create a new Object Storage Repository of type Amazon S3 Compatible and enter the appropriate details.

Instant VM Recovery and Data Offload

Once a Job is configured to use the SOBR, backups can be moved or copied into the Capacity Tier, which sits on a super-decentralized, distributed storage layer leveraging BlockChain technology. This allows for instant VM recovery and data offloading straight from Object Storage.

Conclusion

FileBase’s innovative approach to decentralized object storage offers numerous benefits for backup and recovery solutions. By leveraging BlockChain technology and cryptographic SLAs, FileBase provides a secure, transparent, and highly available storage solution that is perfect for the growing demands of the backup and recovery industry. As the use cases for decentralized storage continue to evolve, FileBase is well-positioned to lead the charge towards a more secure, reliable, and decentralized future for backup and recovery.

Leveraging Generative AI for Unconventional Side Projects: The Power of Prompt Engineering

As a passionate advocate for the transformative potential of generative AI, I recently had the opportunity to share my journey and insights on the “90 Days of DevOps” YouTube channel as part of Michael Cade’s 2024 version of the challenge. My unconventional side project, Find My Black Pudding, served as the perfect example of how prompt engineering can help bring your dreams to life. In this follow-up post, I dive deeper into the topic of prompt engineering and explore its potential for transforming your side projects into tangible realities.

The Journey Begins

It all started with a simple domain registration for FindMyBlackPudding.com. As a British expat living in the United States, I had grown tired of searching far and wide for my favorite breakfast delicacy, black pudding. With no easy way to locate it outside of the UK, I set out to create an app that would help fellow enthusiasts find their nearest black pudding serving based on their location.

From Idea to Reality with Generative AI

Leveraging the power of ChatGPT, a generative AI platform, I was able to prompt engineer my way to a working location-based search platform based on Python. The process was not without its challenges, but the results were well worth the effort. With ChatGPT’s assistance, I was able to create a fully functional and relatively complex app that has the potential to revolutionize the way we find and enjoy black pudding.

The Art of Prompt Engineering

Prompt engineering is an essential skill for anyone looking to leverage generative AI in their projects. It involves crafting queries and instructions in a way that elicits the most useful and creative responses from AI models. Through my experience with Find My Black Pudding, I have gained valuable insights into the art of prompt engineering and its potential for transforming side projects into tangible realities.

Tips for Leveraging Prompt Engineering

If you’re looking to embark on a similar journey, here are a few tips to keep in mind:

1. Start small: Begin with a simple idea and gradually build upon it. Don’t be afraid to start small and refine your queries as you go.

2. Be specific: The more specific your prompts, the more targeted the responses will be. This is especially important when working with generative AI models.

3. Use conversational language: Prompt engineering is all about crafting natural language queries that elicit helpful responses from AI models. Use conversational language to make your queries feel more human-like and relatable.

4. Experiment with different prompts: Don’t be afraid to try out different prompts and see how the AI model responds. This can help you refine your approach and elicit more useful responses.

5. Embrace failure: Not every attempt at prompt engineering will be successful, but that’s okay. Embrace failure as an opportunity to learn and improve your approach.

The Power of Generative AI

The advent of generative AI platforms like ChatGPT has opened up a world of possibilities for side projects like Find My Black Pudding. With the right prompts, these models can help us create everything from simple apps to complex systems. The key is to understand the art of prompt engineering and how to use it to your advantage.

In conclusion, my journey from idea to reality with Find My Black Pudding serves as a testament to the potential of prompt engineering and generative AI. With the right tools and a willingness to experiment, anyone can bring their side projects to life in ways they never thought possible. So go ahead, embrace your creativity, and see where the power of prompt engineering takes you!

Custom Versions of ChatGPT Introduced by OpenAI: A New Way to Interact with Technology

In November 2023, OpenAI introduced custom versions of ChatGPT that combine instructions, extra knowledge, and any combination of skills. This new feature allows users to create tailored versions of ChatGPT for specific tasks or purposes. The idea behind this extension is to provide a more helpful and efficient way of interacting with technology.

Creating Custom GPTs

To create a custom GPT, users can start a conversation with ChatGPT and give it instructions and extra knowledge. They can then pick what the AI can do, such as searching the web, making images, or analyzing data. This process allows users to create a personalized version of ChatGPT that can assist them in their daily lives or at work.

Custom GPTs can be used for various tasks, such as learning the rules of board games, teaching children math, or designing stickers. The possibilities are endless, and the power of Generative AI is now more accessible than ever before.

Example: Integrating Veeam Service Provider Console API with ChatGPT

To demonstrate the potential of custom GPTs, let’s consider an example of integrating the Veeam Service Provider Console API into ChatGPT. This Proof of Concept (PoC) shows how to interact with the API using OpenAPI Schema and simulate actions defined in the schema.

To start, we need to create a new GPT from the ChatGPT editor. We can then configure the Schema by adding the Veeam Service Provider Console API endpoints and defining the actions we want to simulate. Once we have tested the Schema and confirmed that it is working as expected, we can save the Custom GPT and publish it for others to use.

Potential Applications of Custom GPTs

The possibilities for custom GPTs are vast, and they have the potential to revolutionize how we interact with technology. Some potential applications include:

1. Company/Tenant manipulation: Asking for company details and enabling or disabling services.

2. Automation of tasks: Preparing servers for upgrades, patching, and updating.

3. Enhancing platform operations: Conversing with systems as if they were colleagues, making technology more accessible and efficient.

4. Innovation: Creating a connection that feels genuinely human, potentially leading to limitless possibilities for innovation.

Trust and Security Considerations

As with all discussions around AI, there are still many unknowns around security and trust when it comes to custom GPTs. Can we trust this sort of interface with complex, critical tasks? These are important questions that need to be addressed as we continue to refine and expand these capabilities.

Conclusion

Custom GPTs mark a potential shift in how we engage with technology, moving towards interactions that are more natural, intuitive, and efficient. The Proof of Concept of integrating the Veeam Service Provider Console API into ChatGPT gives us a glimpse at the potential that lies in conversing with our systems as if they were colleagues rather than just machines. As we continue to refine and expand these capabilities, the potential for innovation is limitless, promising a future where technology becomes less complex, more efficient, and more user-friendly.

Automation has been a driving force throughout human history, from the wheel to the printing press. With the rise of Generative AI, we have reached a new level of efficiency and innovation.

One example of assisted development was with Microsoft Exchange 2007, which provided PowerShell output that could be copied and pasted. This allowed for more efficient automation and provisioning of tenants and mailboxes.

Over the years, tooling has evolved to help platform engineers, DevOps, and software developers create code more efficiently. However, with the rise of Generative AI, we have reached a new level of efficiency and innovation.

With the new enhanced set of APIs in Veeam Backup & Replication 12.1, it is now possible to automate tasks that would normally be multi-stepped processes through the UI using Python code and Prompt Engineer.

A Prompt Engineer specializes in crafting queries or prompts that guide AI models like ChatGPT or Midjourney to produce specific desired outcomes. This new role requires a deep understanding of the AI model’s capabilities, nuances, and how different prompt structures can affect the output.

To be successful as a Prompt Engineer in technology, one must have a good understanding of what they want to achieve and be able to guide the LLM to produce the desired outcome. This involves manipulating and troubleshooting the output until it meets the desired requirements.

Generative AI has revolutionized the way we approach automation and development. With the ability to craft queries and prompts that guide AI models, we can now achieve outcomes that were previously unimaginable. However, this new technology also requires a deep understanding of the capabilities and limitations of these models. As we continue to push the boundaries of what is possible with Generative AI, we must also be mindful of the ethical implications of these technologies. Automation has always been about finding more efficient ways to achieve our goals, but with Generative AI, we have reached a new level of efficiency and innovation that will shape the future of humanity.

As a technologist, I have always been fascinated by the intersection of technology and content marketing. Recently, I had the opportunity to join host Jeremy Balius on the Filament podcast, where we discussed my journey as a professional tech marketer and the challenges of communicating complex technical topics in a relatable way.

I started my career in tech support, which laid the foundation for my progression through various technical roles. Each role presented new challenges and opportunities to learn, ultimately leading me to Veeam Software, where I currently serve as the Regional CTO for APJ.

One of the key aspects we discussed on the podcast was how a CTO approaches content marketing. In today’s tech landscape, it is crucial to distill complex technical topics into understandable content that resonates with diverse audiences. This not only aids in clear communication but also ensures that technical details are aligned with overarching business outcomes.

We also talked about the intricacies involved in launching a major product like Veeam’s V12. The process requires a fine balance between technical information and market-driven messaging, creating content that resonates with both technical enthusiasts and decision-makers in the business sector.

As someone who is often the target of B2B marketing efforts, I shared insights into the types of approaches that fail to make an impact and emphasized the value of relationship-based marketing. For me, a compelling and relevant technology proposition is key to capturing my interest, rather than a direct sales pitch.

Looking forward to 2024, I foresee a year of growth and consolidation in Veeam’s market positioning. Our focus will be on cybersecurity within our ecosystem, striking a balance between being a key player and maintaining our core identity as a backup company. Personally, I aim to continue my engagement with the tech community through my podcast, Great Things with Great Tech, and bring more tier-one vendors onto the show.

Overall, this podcast episode was a great opportunity for me to share my thoughts on the intersection of technology and content marketing. It’s a space where I continue to learn, grow, and contribute. As I look ahead to 2024, I am excited about the opportunities that lie ahead and the potential for innovation and growth in the tech industry.

2024: The Year of Cyber Resilience

As we step into 2024, the technological landscape is more complex and interconnected than ever before. With the burgeoning field of generative artificial intelligence (AI) and the proliferation of intelligent applications, the world is accelerating at an unprecedented pace. As a result, businesses must navigate a gauntlet of emerging trends and looming challenges. In my role at Veeam, I have been peering over the horizon to anticipate how these developments might interlace with the intricate tapestry of data protection.

Cloud’s Transformation

The cloud’s narrative has always been one of transformation, but as we’ve entered 2024, it’s undergone a more nuanced metamorphosis. The wide recognition of cloud services as a bastion for reducing IT costs has encountered a shifting paradigm. Companies are increasingly drawn back towards private infrastructures as they seek to reclaim command over their digital assets. This retreat is not a retreat at all but rather a strategic repositioning, favoring flexibility and bespoke data management solutions. The delicate balance between the seemingly boundless offerings of public cloud providers and the grounded reliability of on-premises infrastructure is being meticulously reevaluated.

AI: Double-Edged Sword

The cybersecurity threats that loom over 2024 are not just shadows but stark realities. The previous year saw numerous businesses, including prominent Australian personal loan and finance service provider Latitude, succumbing to breaches that laid bare the personal information of millions. These incidents serve as grim reminders of the persistent nature of cyber threats—an arms race that’s only intensifying. The recent Veeam Ransomware Trends Report casts a spotlight on a disquieting truth: while the majority of organizations have security strategies in place, less than half believe in their efficacy. This gap between preparation and confidence has never been more glaring.

The AI that drives our innovation has become a double-edged sword, with advancements in machine learning creating as many vulnerabilities as they aim to protect. The rise of deepfakes and their potential misuse adds another layer of complexity to an already intricate security landscape. As 2024 unfolds, the ethical considerations surrounding AI’s capabilities take center stage.

Cultivating Cyber Resilience

Against the backdrop of these challenges, the cultivation of cyber resilience has emerged as a cornerstone of modern cybersecurity strategy. It’s a multifaceted approach that begins with the most fundamental asset of any organization: its people. Empowering employees through regular training and upskilling is more than a best practice—it’s an imperative. When personnel are adept at recognizing the signs of phishing or suspicious activities, they transform into the first line of defense.

Complementing this human-centric approach is the strategic application of AI. Beyond its established role in data analysis, AI is increasingly being harnessed to detect the subtle signals that herald ransomware and other cyber threats. These technologies can provide an added layer of defense against threats, enabling businesses to anticipate and respond to attacks more proactively.

Balancing Innovation and Security

In conclusion, 2024 is shaping up to be a year of balance. Balance between embracing innovation and maintaining flexibility, between extending our reach into the cloud and guarding the sanctity of our data. As businesses chart their course through these uncharted waters, the equilibrium between these elements will serve as the compass by which they navigate.

As we continue to push the boundaries of what’s possible, we must also remain steadfast in our commitment to security, privacy, and ethical responsibility. The tech trends of 2024 will undoubtedly bring new opportunities and challenges, but with a balanced approach, businesses can not only survive but thrive in this ever-evolving landscape.

As we enter the year 2024, it is clear that generative AI and Large Language Models (LLMs) will continue to be a major focus for technology advancement. However, as these technologies evolve, it is essential to ensure that they do so in a way that prioritizes data privacy and protection.

One of the most significant challenges facing LLMs is the need to balance their utility with the importance of protecting sensitive data. The rapid advancement of LLMs has created new opportunities for generating content, but it also raises concerns about the potential misuse of this data. As a result, organizations must take a proactive approach to ensuring that their use of LLMs aligns with ethical principles and prioritizes data privacy.

One way to address this challenge is through the development of private LLMs, which operate within controlled environments and are designed to function without exposing sensitive data to external vulnerabilities. These models offer more control over the training, fine-tuning, and application of LLMs, ensuring that organizations can unleash their potential while keeping their data protection promises to users.

Another critical aspect of integrating LLMs into our technological landscape is the need for adaptable data privacy frameworks. As we continue to innovate with these models, we must ensure that our data handling practices evolve alongside them. This means adopting scalable security measures capable of protecting vast amounts of data and implementing real-time monitoring and auditing to ensure compliance and security.

Furthermore, as we leverage LLMs more extensively, it is crucial to cultivate a culture of security awareness among all stakeholders. This includes every member of an organization, from the C-suite to the newest inside sales representative, being equipped to protect sensitive data and understand its value. Incorporating these data protection principles will add another layer of trust to the use of LLMs, assuring stakeholders that their privacy is considered and their data is shielded by evolving protective measures.

As we expand our use of LLMs, our commitment to data protection must become a beacon of trust and reliability in an uncertain technological landscape. Private LLMs could well be the vanguard of this new era in technology, representing a blend of innovation and privacy while reaping the benefits of generative AI.

As industry leaders, policymakers, and technologists, we have the responsibility to advocate for, develop, and implement LLM solutions that prioritize data protection as much as they do technological advancement. By doing so, we can ensure that our technological progress reflects our values and sets a positive precedent for the future of technology and privacy.

In conclusion, embracing LLMs and generative AI presents both opportunities and challenges in 2024 and beyond. As we leverage these platforms more, we must do so with a new sense of understanding, responsibility, and a new level of understanding around the principles of privacy and data protection. With the right approach, this exciting time for data and content generation driven by AI from LLMs can be a positive force for progress while prioritizing our values.