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Trend Micro Unveils Vision One Platform with Powerful Gen AI Integration

Leading cybersecurity provider, Trend Micro Incorporated, has long been incorporating artificial intelligence (AI) into its technologies. However, it is now equipped with the capabilities of generative AI, marking a significant advancement in its offerings.

Today, Trend Micro has introduced its new Vision One platform, which brings together a range of cybersecurity capabilities, including extended detection and response (XDR), attack surface risk management (ASRM), and zero trust. This platform represents an evolution of the previously announced Trend Micro one platform in 2022, with the noteworthy addition of gen AI.

One notable feature of the Vision One platform is the gen AI-powered companion called Trend Vision One. This companion serves as an assistant for security operation center (SOC) analysts, enabling them to utilize natural language queries to obtain answers, facilitate threat hunting activities, and expedite remediation processes.

Kevin Simzer, COO of Trend Micro, expressed the company’s commitment to leveraging the power of gen AI within the security operation center. He emphasized the challenging nature of the SOC environment, where analysts are often overwhelmed with vast amounts of telemetry from diverse sources.

By harnessing the potential of gen AI, Trend Micro aims to alleviate the stress faced by SOC analysts and empower them with an intelligent assistant that can streamline their workflows. The integration of gen AI into the Vision One platform exemplifies Trend Micro’s dedication to delivering cutting-edge solutions that enhance cybersecurity operations and provide effective defense against emerging threats.

Why Gen AI is Good fit for the SOC

A lot of data and alerts are continuously flowing into the average SOC.

AI has long had a role in technology platforms from vendors including Trend Micro to help filter through all the noise and find patterns, anomalies and potential risks. What SOC analysts still have to do is understand what the data actually means and know the right commands, scripts and tools to get the desired result.

Simzer explained that the companion is an optional tool that organizations can choose to turn on as part of Trend Vision One. Part of an SOC analyst’s job is to perform threat hunting across the environment, looking for potential risks.

“Our companion capability will allow the SOC analyst to actually do threat hunting in a much more effective way,” Simzer siad. “The SOC analysts can input natural language and it will form the complex XDR queries that need to run.”

SOAR integration

XDR queries are an often complex set of command and scripting needed to search across all the data a cybersecurity platform collects to find matches for a given set of criteria and circumstances that could be indicative of a particular threat.

In recent years, SOCs have been increasingly integrating security orchestration, remediation and response (commonly known by the acronym SOAR) technologies in a bid to automate security. Simzer said that SOAR is also built into the Vision One platform and can potentially benefit from the gen AI companion.

Gen AI is also helping Trend Micro itself as it looks to optimize customer support. Simzer said that Trend Micro is using the technology to build out knowledge-based articles on how technologies work. He explained that Trend Micro’s customer support people are now using gen AI to help provide recommendations and answer user questions.

What’s under the hood? Microsoft Azure OpenAI

While Trend Micro has been developing its own AI capabilities as part of its portfolio for years, the new gen AI capabilities are powered by the Microsoft Azure OpenAI service.

“We’ve been using AI for over a decade; it’s not like we didn’t have data scientists, but there’s no question gen AI really fast forwards a ton of innovation and we jumped on it fairly quickly,” Simzer said. “We have plans down the road to actually have our own gen AI, but the immediate benefits of what we could get with OpenAI were just so real that we couldn’t pass it up.”

A key issue for any organization with gen AI is privacy, which is a high priority concern with cybersecurity information. Simzer said that Trend Micro has been very careful and diligent to ensure that customer data remains private.

“We’ve been training and tuning it and building the guardrails to make sure that none of our customer data is ever introduced into the Azure OpenAI environment,” he said. “We really wanted to be methodical and responsible about it.”

Oracle Corporation Expands into Generative AI Services

In a move to capitalize on the growing demand for generative AI services, Oracle Corp., renowned for its expertise in database technology, announced a strategic partnership with Toronto-based startup Cohere. The collaboration aims to develop a new cloud service that enables enterprise customers to create and train large language models (LLMs) using their private data while ensuring data privacy and security.

Oracle’s founder and chief technology officer, Larry Ellison, confirmed the partnership during the company’s recent earnings call, where he highlighted Oracle’s substantial growth in the cloud business. The longstanding relationship between Oracle and Cohere, along with Oracle’s participation in Cohere’s recent $270 million Series C funding round, has fueled speculation about this collaboration.

Ellison emphasized the vision behind the partnership, stating, “Cohere and Oracle are working together to make it very, very easy for enterprise customers to train their own specialized large language models while protecting the privacy of their training data. Over the next few years, lots of companies are going to train their own specialized large language models.”

As part of the collaboration, Oracle’s internal application development teams have already started utilizing the Cohere AI cloud service on the Oracle Cloud Infrastructure (OCI). The service leverages Oracle’s private data to fine-tune and expand existing Cohere LLMs. Notably, this supplementary training has resulted in the creation of two new specialized LLMs, catering to medical professionals and first responders, respectively.

With Oracle’s significant presence in the healthcare sector following its acquisition of healthcare giant Cerner in 2022, the company recognizes the potential of specialized large language models to enhance the productivity of highly trained professionals. Ellison emphasized the impact of these models, stating, “Specialized large language models will be instrumental in helping highly trained professionals use their precious time more efficiently.”

The collaboration between Oracle and Cohere signifies Oracle’s commitment to exploring new avenues within the enterprise cloud space and capitalizing on the potential of generative AI services. As the partnership progresses, enterprises can look forward to an easier and more secure way of training their own customized language models, tailored to their specific needs and domains.

Oracle is no stranger the World of AI

While the upcoming service with Cohere is new, Oracle is quite familiar with the world of AI. In fact, Ellison made sure to emphasize during the earnings call that Cohere is using Oracle Cloud for training LLMs.

Ellison said that Oracle has an edge over its competitors because it had more experience and expertise in handling large amounts of data securely and efficiently. Other vendors that have publicly revealed they use Oracle Cloud for training LLMs include Adept AI Labs, which raised $350 million in March for a generative AI service for using software. Oracle also has a cloud AI partnership with Nvidia, that involves Nvidia GPU hardware and Nvidia using the Oracle Cloud to help with ongoing AI development. All told, Ellison boasted that Oracle Cloud is already a multi-billion business for AI workloads.

“In the aggregate, our generative AI cloud customers have recently signed contracts to purchase more than $2 billion of capacity in Oracle’s Gen2 Cloud,” Ellison said.

While the numbers are large and growing, in the cloud business Oracle still trails behind the big three hyper-scalers which all have their own generative AI services. Amazon Web Services (AWS) announced its Bedrock generative AI services in April, Google has a host of its own services and models that were updated at its recent I/O conference, and Microsoft benefits from its tight partnership with OpenAI.

Microsoft Adds AI Voice Chat to Bing on Desktop

Microsoft has expanded its voice capabilities by introducing voice support for Bing Chat on desktop. Users can now interact with the search engine’s chatbot on Edge for PCs, utilizing OpenAI’s GPT-4 technology. This feature was initially available for Bing’s AI chatbot on mobile apps and has now been extended to desktop users. By simply tapping on the microphone icon in the Bing Chat box, users can engage in voice conversations with the AI-powered bot.

In its latest Bing preview release notes, Microsoft acknowledged the popularity of voice input for chat on mobile devices and highlighted the addition of voice support to the desktop version. Currently, the feature supports English, Japanese, French, German, and Mandarin, with plans to expand language support in the future. Users can now ask Bing questions verbally and receive text-to-speech responses from the chatbot, which can also answer questions using its own voice. For instance, Microsoft suggested asking Bing Chat, “What’s the toughest tongue twister you know?” and receiving a spoken response.

The introduction of voice support for Bing Chat on desktop comes shortly after Microsoft’s announcement about discontinuing the standalone Cortana app for Windows, which functions as a voice assistant. Microsoft emphasized that users will still have access to powerful AI capabilities in Windows and Edge, mentioning Bing Chat and Microsoft 365 Copilot as examples. Bing Chat, combined with AI capabilities, provides users with voice interaction and productivity features, while Microsoft 365 Copilot utilizes artificial intelligence to generate content within the company’s applications.

With voice support now available on Bing Chat for desktop, users can enjoy a more interactive and convenient search experience, enabling them to converse with the AI chatbot using voice input and receive spoken responses.

PhotoRoom and Google Cloud: Democratizing AI Photo Editing

AI-driven photo editing app, PhotoRoom, has entered into a partnership with Google Cloud to leverage Google Cloud’s A3 instances, powered by Nvidia GPUs, and their expertise in scaling large AI models. This collaboration aims to bring high-quality image editing capabilities to a wider range of businesses through generative AI. By utilizing Google Cloud’s support, PhotoRoom expects to significantly accelerate its content delivery process.

With the newly integrated generative AI capabilities, PhotoRoom claims to reduce the time required to produce photography content to under an hour, while ensuring exceptional accuracy and quality. This advancement will have a substantial impact on small businesses (SMBs) and entrepreneurs, as it improves speed and scalability, thereby reducing the time and costs involved in creating and editing commercial photography.

Matthieu Rouif, co-founder and CEO of PhotoRoom, explained the benefits of generative AI for SMBs, stating, “By leveraging generative AI, we aim to benefit small businesses by enabling them to generate high-quality product photos quickly and affordably. Our AI model allows users to create entire scenes around a product, all based on a single smartphone photo. This process reduces the need for studio photography, which would cost thousands of dollars for small businesses.”

This partnership builds upon PhotoRoom’s recent introduction of its Instant Backgrounds and Instant Shadows features, both powered by AI technology, designed to enhance product shots. By democratizing the use of generative AI, PhotoRoom aims to empower small and medium-sized businesses with cutting-edge technologies, enabling them to compete in the digital space.

Through the collaboration between PhotoRoom and Google Cloud, businesses of all sizes can harness the power of AI-driven photo editing, enabling them to create high-quality visual content efficiently and affordably. The democratization of generative AI in the realm of photography holds tremendous potential for transforming the way businesses approach their visual marketing strategies.

Using AI in PhotoRoom to Enhance Photo Editing Speed

PhotoRoom’s Rouif said that the company incorporated a trained diffusion AI model into its platform to generate images specifically for ecommerce and product photography. The integration of Google’s computing power and memory capacity now enables the application to achieve swifter, more precise and more scalable image creation.

“For small businesses, time is money, and PhotoRoom is 10 times faster than other generative solutions: generating AI images in one second, compared to 15 seconds on average for Midjourney and DALL-E,” Rouif told VentureBeat. “The efficient scaling offered by Google Cloud’s infrastructure enables us to handle an increasing volume of images worldwide without compromising service quality or performance.”

Moreover, PhotoRoom asserts that its Remove Background feature is 30% more accurate than top photo editing alternatives.

“Once the background is removed, small businesses and entrepreneurs require a realistic background to showcase their product — PhotoRoom’s generative AI technology solves this problem by building instant backgrounds and shadows, which help them create content and lifestyle photography,” added Rouif.

The company stated that it currently processes two billion images annually. Collaborating with Google to scale its GPU infrastructure will enable the company to rapidly enhance and broaden its generative AI product offerings.

“This partnership will help us provide a stable and dependable solution to accommodate the increasing adoption of generative AI in the ecommerce industry,” said Rouif. “Google Cloud’s long-term focus on AI and infrastructure investments and open ecosystem aligns well with PhotoRoom’s vision of making high-quality product photography accessible to all.”

AI Revolution: Unleashing Transformative Power Across Industries

The development of artificial intelligence (AI) has witnessed an undeniable surge in recent months. The emergence of groundbreaking technologies such as large language models (LLMs) like GPT-4, capable of astonishing cognitive feats like excelling on the Uniform Bar Examination, and ASR platforms like ASAPP, achieving remarkable accuracy rates of 98.25%, underscores the relentless pace of progress in the AI domain. It is evident that the trajectory of AI advancement will only continue to accelerate.

The rapid strides in AI have prompted concerns, with a petition garnering over 27,000 signatures advocating for a moratorium on AI system training. Leading AI researchers, intellectuals, and entrepreneurs have expressed the need for caution when dealing with such potent technology. However, the potential benefits offered by AI are so immense that we are on the brink of witnessing widespread adoption across a multitude of industries and sectors.

The competitive advantages bestowed by AI will expedite its adoption rate, ultimately leading to the technology’s deep integration within the daily operations of countless companies. This transformative shift will fundamentally reshape the distribution of market share, redefine the availability of products and services to customers, and revolutionize how companies position themselves in the global landscape.

As AI continues to evolve, its utilization will become increasingly tailored to specific sectors and use cases, making it an integral part of numerous industries. The implications of this widespread adoption are far-reaching, as AI-driven systems will permeate every aspect of business operations, enabling organizations to unlock unprecedented efficiencies, insights, and opportunities.

The future holds a landscape where AI’s impact is not limited to a select few pioneering companies but becomes the norm across industries. Embracing AI will become a strategic imperative for businesses seeking to remain competitive in this rapidly evolving digital era.

Why AI Adoption Will Be Rapid and Widespread

Intelligence is the most powerful and dynamic resource we have — it’s an engine of innovation, it can be put toward unlimited purposes, and in the case of AI, it even has the potential to be recursively self-improving. One of the reasons AI has generated so much anxiety is the fact that it exhibits the capacities human beings hold most dear: creativity, problem-solving and the ability to express ideas in a cogent and compelling way. However, it’s a mistake to overlook the ways AI and human intelligence complement each other.

Over the past several months, most media attention has been focused on LLMs as millions of people experiment with them and major companies like Google and Microsoft integrate the technology into their products. But AI is set to revolutionize countless other areas — a recent Gartner report considered the top five use cases in finance alone: demand/revenue forecasting, anomaly and error detection, decision support, POC revenue forecasting and cash collections. These use cases enable people to do their jobs more effectively. Revenue forecasting, for instance, allows company leaders to plan more strategically. Error detection helps employees avoid tedious manual analysis and backtracking.

Between 2017 and 2022, McKinsey reports that AI adoption more than doubled. Gartner found that 45% of executives say the publicity of ChatGPT led to an increase in AI investment, while 70% of companies are exploring generative AI. With more resources flowing into AI research and use cases growing all the time, this trend shows no sign of slowing down.

The expanding business case for AI

There’s a corollary to the ever-growing set of use cases for AI: Drastic improvements in business outcomes. According to a recent PwC survey, companies that have distinguished themselves as “AI leaders” are extracting significant value from the technology in many areas: increasing productivity through automation, improving decision-making and the customer experience, developing more innovative products and services, and enhancing employee experience and skills acquisition (this list only encompasses the top five outcomes).

Consider natural language processing (NLP): AI can now flawlessly convert speech to text, extract sentiment and meaning from huge volumes of consumer data and immediately provide credible responses to customers’ questions. The global call center market is expected to grow from almost $340 billion in 2020 to $496 billion in 2027, which is no surprise given the billions of dollars spent on these centers by major financial institutions, airlines and telecommunications companies. ASR platforms like ASAPP are dramatically improving automated communications, which will lead to much better customer experiences, efficiency gains and cost reductions (as companies won’t have to spend as much on human capital).

Companies are becoming more confident in their ability to predict the ROI they can secure from AI — 72% of AI leaders say they can confidently assess the ROI of current AI initiatives, while 59% say the same about initiatives planned for the next year. There’s no clearer sign that the business case for AI is becoming stronger by the day.

AI has become integral to more and more daily operations

Although we’re still years away from roads filled with fully autonomous vehicles and other elements of the AI-powered future that have long captured the public imagination, the breakthroughs of the past six months alone have demonstrated that it’s extremely difficult to predict just how quickly this field will develop. As AI and ML evolve in tandem with sweeping advances in robotics and automation, the economic impact will be tectonic.

Beyond the breadth of AI adoption across industries and sectors, companies will increasingly find that AI is integral to a growing range of functions. Everything from product development to operations to accounting, sales and pricing will be affected by AI, and companies will be divided into AI haves and have-nots.

Take hiring, for instance — 85% of companies that use AI for HR-related purposes say it helps them increase efficiency, while more than two-thirds report that it has improved the quality of applications for review. Speaking of human capital, there’s a global hiring boom in AI right now, which will give some companies a serious competitive advantage in the coming years while others fall behind.

AI will function as a turbocharger for many aspects of business, but companies won’t be able to leverage this performance boost if they continue to use cumbersome and overly complex legacy systems. Just as it wouldn’t make sense to strap a turbocharger onto a horse and buggy, it doesn’t make sense to deploy AI without the right supporting tech stack — from efficient workflow solutions to feature-rich and accessible customer-facing platforms (that is, your contact center UI).

The acceleration of AI innovation and adoption will catalyze soaring investments in the technology, and billions of dollars in valuations will shift as some companies use AI to drive competitive differentiation and others fail to keep pace. Companies that embrace AI will figure out new and productive ways to integrate it with their existing workforces, products, and operations — a head start today that will pay dividends tomorrow.

NVIDIA Unveils ‘Grace Hopper’: Next-Gen CPU+GPU Chip for AI Models

NVIDIA, renowned for its advancements in artificial intelligence (AI), has introduced its latest CPU+GPU chip, Grace Hopper, which promises to usher in the next era of AI models and chatbots.

While traditionally known for their role in accelerating graphics rendering for computer games, graphics processing units (GPUs) have demonstrated significantly higher computing power compared to central processing unit (CPU) chips. This led tech companies to adopt GPUs for training AI models due to their ability to perform multiple calculations simultaneously, in parallel.

In 2020, NVIDIA introduced the A100 GPU chip, which proved instrumental in training early iterations of conversational chatbots and image generators. However, within just a short span, the highly advanced H100 Hopper chips have emerged as essential components in data centers that power popular chatbots like ChatGPT. Now, NVIDIA has unveiled a groundbreaking chip that integrates both CPU and GPU capabilities.

The Grace Hopper chip represents a significant leap forward, combining the strengths of CPU and GPU technologies to enhance AI model training and performance. Its introduction marks a new milestone in the ongoing development of AI hardware, enabling more efficient and powerful computing capabilities for AI-related applications.

As the AI landscape continues to evolve, NVIDIA’s Grace Hopper chip aims to play a pivotal role in driving advancements in AI models and chatbot technologies, propelling the field toward unprecedented possibilities.

What are Grace Hopper chips from Nvidia?

According to a press release, Nvidia has created its new chip by combining its Hopper GPU platform with the Grace CPU platform (both named after Grace Hopper, a pioneer of computer programming). The two chips have been connected using Nvidia’s NVLink chip-to-chip (C2C) interconnect technology.

Dubbed GH200, the super chip has 528 GPU tensor cores which can support 480 GB of CPU RAM and 96 GB of GPU RAM. The GPU memory bandwidth on the GH200 is 4TB per second, which is twice as much as the A100 chips.

The super chip also boasts 900GB/s of the coherent memory interface, which is seven times faster than the latest generation PCIe, which has only become available this year. Along with running all Nvidia software such as HPC SDK, Nvidia AI, and Omniverse, the GH200 has 30 times higher aggregate memory bandwidth compared to the A100 chips.

What will chips be used for?

Nvidia, well on its way to becoming a trillion-dollar company, expects the GH200 chips to be used for giant-scale AI and high-performance computing (HPC) applications. At this point in time, one can only imagine AI models and chatbots that are faster and more accurate being built with this superior technology.

The company also plans to use them to build a new exaflop supercomputer capable of performing 10¹⁸ floating point operations per second (FLOPS). Two hundred fifty-six of the GH200 chips will be put together to function as one large GPU and have 144 TB of shared memory, about 500 times that of the A100.

“Generative AI is rapidly transforming businesses, unlocking new opportunities, and accelerating discovery in healthcare, finance, business services, and many more industries,” said Ian Buck, vice president of accelerated computing at NVIDIA, in a press release. “With Grace Hopper Superchips in full production, manufacturers worldwide will soon provide the accelerated infrastructure enterprises need to build and deploy generative AI applications that leverage their unique proprietary data.”

Global hyperscalers and supercomputing centers in the U.S. and Europe will get access to the GH200-powered systems later this year, the release added.

AI Regulation: Two Bipartisan Bills Introduced in US Senate

As artificial intelligence (AI) continues to experience rapid growth, governments around the world have started to consider modifying policies and regulations around the technology, US Senators yesterday introduced two separate bipartisan bills addressing AI to tackle issues surrounding the technology and to remain “competitive”, according to Reuters.

One bill would require the US government to be transparent when using AI when interacting with people.

The other bill would establish an office to determine whether the US was competitive in the latest technologies. Additionally, the proposed bill would mandate agencies to create a way to enable people to lodge appeals against decisions made by AI.

Reaching solutions

Homeland Security committee chair, Democrat Senators Gary Peters along with Republicans – Senators Mike Braun and James Lankford, introduced a bill that would require US government agencies to tell individuals when the agency is using AI to interact with them.

Senator Mike Braun said, “The federal government needs to be proactive and transparent with AI utilization and ensure that decisions aren’t being made without humans in the driver’s seat.”

Democrat Senators Michael Bennet and Mark Warner further introduced a measure along with Republican Senator Todd Young.

Under the new measure, an Office of Global Competition Analysis would be established through which the agency would ensure that the US remained front and center in developing artificial intelligence.

“We cannot afford to lose our competitive edge in strategic technologies like semiconductors, quantum computing, and artificial intelligence to competitors like China,” Michael Bennet said.

Meanwhile, the UK has joined the race to propose regulatory solutions for AI technology. The UK is set to host a global summit on artificial intelligence safety later this year.

Britain’s Prime Minister Rishi Sunak announced on Thursday at a joint press conference with US President Joe Biden that the two countries would work together on AI safety.

Industrial insight

With ChatGPT, an AI program frequently making headlines this year, lawmakers around the world have had to address issues regarding the use of such technology.

Recently, OpenAI CEO Sam Altman addressed a Senate panel saying that he is willing to work with regulators and develop frameworks to reduce potential harm from AI.

“I think we also need rules, guidelines, on what’s expected in terms of disclosure from a company providing a model,” he said. “I am nervous about it”, he added.

Altman’s testimony was one of many at the Senate as the White House invited top technology CEOs to address AI concerns with U.S. lawmakers seeking to further the technology’s advantages, while limiting its misuse.

Altman’s warnings about AI and elections come at a time when companies large and small have been competing to bring AI to market, with billions of dollars at play. But experts everywhere have warned that the technology may worsen societal harms such as prejudice and misinformation.

Some have even gone so far as to speculate AI could end humanity itself.

US at Risk of Losing AI Edge to China, Says Scale AI CEO

The US is at risk of losing its edge to China in the race for artificial intelligence (AI), according to Alexandr Wang, the CEO of Scale AI. Wang was speaking at a summit organized by the company for government officials, Bloomberg reported.

AI is among the future technologies that countries around the world are looking to establish their supremacy in as the world evolves into the next age. Interesting Engineering has previously reported that China has been denting U.S. dominance in the technology sector. In studies conducted by policy institutes, China has already established monopolies in certain areas.

Not only is China home to the leading research institutes of a large spectrum of topics, but it is also generating nearly half of the world’s most impactful papers in these areas. When it comes to AI, the U.S. is still ahead but at risk of losing its lead, according to Wang.

What does Scale AI do?

The U.S. lead in AI has been demonstrated by the unveiling of ChatGPT, the conversational chatbot that multiple companies in China have tried to replicate but without the resounding popularity.

While OpenAI is credited with creating GPT, the large language model (LLM) behind ChatGPT, the role of companies like Scale AI cannot be discounted. LLMs need tons of data to train the bots, and the bot is only as good as the data it is trained on.

In 2016, Alexander Wang dropped out of MIT and founded Scale AI to help companies get the right training data to train their models. Apart from OpenAI, the company is also helping chipmaker Nvidia, carmaker Toyota, and the U.S. government build better AI systems.

How the U.S. is losing its edge

According to Wang, AI is unavoidable technology that must be integrated into military operations to stay ahead of adversaries. Comparing AI to nuclear weapons, Wang said that the technology would reshape global diplomacy and power.

Wang also pointed out that China was investing heavily in AI, both in terms of absolute numbers as well as relative to its defense budget. In a presentation at the summit, Wang detailed that the People’s Liberation Army had invested $1.6 billion in the technology in 2020, compared to the $1.3 billion allocated by the Department of Defense.

Senator Mike Rounds, speaking at the same event, agreed that the U.S. currently held the advantage when it came to data collection and labeling but also warned that services like TikTok, which is owned by Chinese company ByteDance could give the Chinese access to additional English language samples to train their AI systems.

Interesting Engineering has also reported that the flurry of AI models developed by Chinese tech counterparts after ChatGPT’s success has also been bilingual and intended for users outside China.

Wang further added that the U.S. must leverage the vast amounts of data it collects through its military hardware, such as sensors, cameras, and satellites, to train AI. Ensuring the quality of the inputs can turn the “hardware advantage into data advantage.”

FBI Warns of Increasing Threat: AI Deepfakes and Sextortion Cases Surge

In a recent Public Service Announcement (PSA), the Federal Bureau of Investigation (FBI) cautioned the American public about a concerning rise in incidents of sextortion and online harassment facilitated by the use of artificial intelligence (AI) deepfake technology. Malicious actors are exploiting AI algorithms to manipulate digital media, creating realistic deepfakes that enable them to target unsuspecting victims.

Deepfakes are synthetic content generated through AI and machine learning techniques, capable of making individuals appear to say or do things they have never done. These deceptive creations have become alarmingly authentic, leading to severe consequences for those targeted.

The FBI has been receiving reports from various victims, including minors and non-consenting adults, whose social media content has been maliciously altered to explicit material. These doctored images and videos often circulate widely on social media platforms or end up on pornographic websites.

“The photos are then sent directly to the victims by malicious actors for sextortion or harassment, or until it was self-discovered on the internet. Once circulated, victims can face significant challenges in preventing the continual sharing of the manipulated content or removal from the internet,” the FBI emphasized in their PSA.

With readily available photo-editing software like Adobe’s Photoshop, which now incorporates generative AI capabilities, and OpenAI’s DALL-E, manipulating images has become increasingly accessible and convenient.

Neil Sahota, a United Nations AI adviser, highlighted the severity of the issue, stating, “We hear the stories about the famous people, but it can actually be done to anybody. And deepfake actually got started in revenge porn. You really have to be on guard.”

Sahota further advised individuals to remain vigilant and look for irregularities in videos and audio that may indicate manipulation. Unusual body language, odd shadowing, or inconsistencies in speech patterns should be red flags, signaling potential deepfake content.

The FBI has noticed a surge in victims reporting such crimes. Perpetrators typically employ tactics such as demanding payment in the form of money or gift cards, or coercing victims into providing genuine sexually-themed images or videos. Additionally, they use intimidation by threatening to expose the manipulated content to the victim’s friends and family on social media.

The FBI clarified that sextortion violates several federal criminal statutes, as it involves extorting money or sexual favors from victims through threats of public exposure. The primary motivations for malicious actors engaging in such behavior include entrapping victims into providing more illicit content, harassment, or extracting as much money as possible.

The FBI’s warning urges individuals to exercise caution when using social media platforms. They emphasize the importance of being mindful when posting any content online or sharing personal photos, videos, and information via social media, dating apps, and other online platforms.

“Advancements in content creation technology and the widespread availability of personal images online provide new opportunities for malicious actors to identify and target victims. This exposes individuals to potential embarrassment, harassment, extortion, financial losses, or prolonged victimization,” the FBI stated.

The agency’s message serves as a call to action, encouraging the public to remain vigilant and take necessary precautions to safeguard their online presence and personal information from these emerging threats.

The Transformative Power of AI: Shaping the Future of Living and Working

The pervasive influence of artificial intelligence (AI) has ignited widespread discussions, capturing headlines, dominating social media, and becoming a topic of conversation at dinner tables. While some express concerns about the rapid acceleration of AI and call for a pause in training new systems to fully comprehend their impact, others view AI as the foundation of the fourth industrial revolution—a disruptive force that unlocks unprecedented possibilities for learning, working and living.

However, disruptive technologies have been shaping our lives and work for decades. These transformations have not been without consequences, as economic shifts and social upheaval have often accompanied them. Automation in manufacturing revolutionized mass production and cost efficiencies, e-commerce platforms reshaped the way we shop and conduct business, and online education provided flexible and affordable learning opportunities to millions worldwide.

At present, much of the discussion surrounding AI’s impact remains speculative. Nonetheless, there is a consensus that AI will profoundly affect jobs, and it may even challenge the fundamental nature of work itself. What remains uncertain is how AI will unfold across society in the long run. Will it follow the pattern of past technological revolutions, causing temporary disruptions but ultimately yielding long-term benefits? Or will it act as a catalyst for new forms of learning and upskilling, bridging the digital divide and promoting equality?

One thing is evident: Unlike previous industrial revolutions, we now have unparalleled access to a vast array of learning resources capable of teaching people at scale, empowering marginalized communities, and mitigating the disruptions caused by evolving occupations.