Consumer spend on generative AI apps hit nearly $1 1B in 2024: report

Meta AI Releases the First Stable Version of Llama Stack: A Unified Platform Transforming Generative AI Development with Backward Compatibility, Safety, and Seamless Multi-Environment Deployment

Generative AI, particularly models such as ChatGPT that use large-scale language models (LLM), has introduced a new dimension to cybersecurity due to its high degree of versatility and potential impact across the cybersecurity field[2]. This technology has brought both opportunities and challenges, as it enhances the ability to detect and neutralize cyber threats while also posing risks if exploited by cybercriminals [3]. The dual nature of generative AI in cybersecurity underscores the need for careful implementation and regulation to harness its benefits while mitigating potential drawbacks[4] [5].

To short-circuit the higher education AI apocalypse, we must embrace generative AI – The Hill

To short-circuit the higher education AI apocalypse, we must embrace generative AI.

Posted: Sun, 26 Jan 2025 13:00:00 GMT [source]

The pilots targeted diverse use cases, including officer training, semantic search for investigative data and hazard mitigation. “These pilots taught us valuable lessons about responsible AI use, governance and measuring success,” says Kraft. DHS has summarized those insights in its newly released DHS GenAI Public Sector Playbook. Social media and film and television streaming were the top in-app revenue-producing categories, accounting for $11.7 billion and $11.9 billion in spending, respectively.

Why the latest TikTok ban attempt is different — and what it means for marketers

Sure, a human can show another human how to jump in the air and do the splits, but it won’t especially sink in until the person being shown the demonstration attempts the physical act themselves. In today’s column, I identify and explore a hot trend in the AI field that is variously referred to as Physical AI sometimes also known as Generative Physical AI (a mash-up of generative AI and a said-to-be additional physical AI capability). “AI has the potential to accelerate business objectives and sustainability initiatives,” Garcia notes.

It’s also mainly dominated by two platforms, TikTok and YouTube,which alone make up more than 70% of category consumer spend. Meanwhile, film and television streaming apps monetize through subscriptions, which has led to more competition. Nine different apps account for at least 3% of the overall streaming revenue, and none account for more than 15%. Along with identifying an increase in in-app spending, Sensor Tower’s latest state of the industry report shows that consumers’ time spent on their mobile phones increased by 5.8% YoY in 2024 to a whopping 4.2 trillion total hours worldwide. Wider availability of generative AI platforms led to a massive increase in the category’s revenue take, though it remains behind established stalwarts.

When we communicate, we rely on shared understanding, context, intonation, facial expression, body language, situational awareness, cultural references, past interactions, and many other things. The English language is one of the most literally specific languages in the world, and so a great many other languages will likely have bigger problems with human-machine communication. Chatbots based on Large Language Models (LLMs) are inherently tone-deaf, ignorant of human context, and can’t tell the difference between fact and fiction, between truth and lies. They are, for lack of a better term, sociopaths — unable to tell the difference between the emotional impact of an obituary and a corporate earnings report. The sentence comes to mind when I’m presented, casually, with ideas produced by our new emotionless sidekick “generative AI”.

Consumer Technology Overview

He linked the project to the use of AI for digital health records, noting the technology could help develop customized cancer vaccines and improve disease treatment. AI-powered chat bots have grown in popularity, with an Inside Higher Ed survey this fall showing 50 percent of chief technology officers are building their own chat bots and assistants. McFarland said she envisions a future where AI powers deeper personalization across customer engagement and service. She highlighted the potential of AI to create more intelligent, responsive interactions that not only address customer needs but anticipate them. McFarland said customer service is a “low-hanging fruit” for AI, where tools like interactive voice response (IVR) chatbots and customer service representative (CSR) prompts are improving interactions and reducing costs.

Quantinuum is also exploring the potential of quantum transformers, a model architecture that has revolutionized classical NLP. This website is owned and operated by Informa TechTarget, part of a global network that informs, influences and connects the world’s technology buyers and sellers. The EDT&Partners and AWS teams have been piloting Lecture collaboratively with a handful of universities and EdTechs.

Dell may see larger generative AI server push outs than expected: Loop – Seeking Alpha

Dell may see larger generative AI server push outs than expected: Loop.

Posted: Sat, 25 Jan 2025 13:00:00 GMT [source]

Generative AI is revolutionizing the field of cybersecurity by providing advanced tools for threat detection, analysis, and response, thus significantly enhancing the ability of organizations to safeguard their digital assets. This technology allows for the automation of routine security tasks, facilitating a more proactive approach to threat management and allowing security professionals to focus on complex challenges. The adaptability and learning capabilities of generative AI make it a valuable asset in the dynamic and ever-evolving cybersecurity landscape [1][2]. The concept of utilizing artificial intelligence in cybersecurity has evolved significantly over the years. One of the earliest types of neural networks, the perceptron, was created by Frank Rosenblatt in 1958, setting the stage for the development of more advanced AI systems like feedforward neural networks or multi-layer perceptrons (MLPs)[1]. With the advent of generative AI, the landscape of cybersecurity has transformed dramatically.

This Week In Security: ClamAV, The AMD Leak, And The Unencrypted Power Grid

GenAI will continue to evolve, and IRI is committed to helping both rising and accomplished leaders stay one step ahead of the curve. Sana Hassan, a consulting intern at Marktechpost and dual-degree student at IIT Madras, is passionate about applying technology and AI to address real-world challenges. With a keen interest in solving practical problems, he brings a fresh perspective to the intersection of AI and real-life solutions. The second big challenge also comes with potential job displacement due to the automation of the creative process. As AI gets better at tasks that humans have historically handled, industries must find the right balance to let AI create jobs while saving the workforce/employees from losing work. AI systems are also being used to create a synthetic transaction dataset that will help in fraud detection in real time.

This is a real step change, precipitated by falling cost of innovation, that is proving hugely important because it allows relatively smaller tech-enabled players to unlock the potential of Gen AI technology for their specific business needs. Banks are already widely applying predictive AI to risk scoring, fraud detection and Next Best Offer (NBO) models, which leverage data-driven insights to tailor product recommendations to individual customer needs and preferences. Key advantages include lower costs, reduced energy consumption and improved data transparency and integrity. A new generation of smaller models, such as IBM® Granite™, built on cleaned, filtered datasets for specific tasks, reduce risks such as bias and inappropriate output while increasing data visibility.

For core players like visual effects artists, illustrators, actors, scriptwriters, composers, studio engineers, photographers, game designers, audio and video technicians and animators, GenAI might threaten aspects of their roles. Its abilities include automating tasks such as character and environment design, voice generation and cloning, sound design, tools programming, scriptwriting, animation and rigging. It also handles 3D modeling, music generation and recording, lyrics composition, mastering, mixing and more. Through tools such as ChatGPT and MidJourney, GenAI enables users to create spectacular images, new content and professional-quality videos for free.

Harvey is fine-tuned on vast amounts of legal data, specifically designed to analyze complex scenarios, with some lawyers reporting that they value it for its accuracy and depth. According to the 2023 «International Legal Generative AI Survey» by LexisNexis, nearly half of all lawyers surveyed said they believe generative AI will transform their business, with a staggering 92% anticipating at least some impact. Unlike traditional search engines that rely on keyword searches, GenAI enables researchers to analyze large data sets at scale, quickly identify relevant precedents and summarize key points. In fact, GenAI saves researchers and lawyers time by generating abstracts and analyzing decisions and cases from the vast pool of legal texts it’s trained on. Legal professionals across corporations, law courts and governments use AI-powered tools, such as Spellbook and Juro, to process large data sets, summarize legal briefs and documents, prepare tax returns, draft contracts and personalize correspondence.

Global sports institutions use Granite models, tuned with their own domain data, to enhance fan experiences with AI-generated commentary. Internally, IBM uses Granite models to power its human resources (HR) service platform, AskHR. By using natural language prompts, IBMers can access HR services in one place, saving time for both employees and HR professionals. Generative AI offers significant advantages in the realm of cybersecurity, primarily due to its capability to rapidly process and analyze vast amounts of data, thereby speeding up incident response times. Elie Bursztein from Google and DeepMind highlighted that generative AI could potentially model incidents or produce near real-time incident reports, drastically improving response rates to cyber threats[4]. This efficiency allows organizations to detect threats with the same speed and sophistication as the attackers, ultimately enhancing their security posture[4].

The pace at which companies are building new data centers means the bulk of the electricity to power them must come from fossil fuel-based power plants,” says Bashir. «With Lecture we enable users of Lecture to optimize their infrastructure budgets and deploy some of the latest and most effective LLMs like Claude from Anthropic or Nova from AWS, on-demand, with a simple click of a button and configuration.» Another big challenge banks face in AI adoption is the issue of trustworthiness, specifically preventing hallucinations—errors where AI generates false or misleading information. In a customer-facing environment, such mistakes can damage trust and lead to potentially severe compliance issues, particularly in highly regulated industries like banking. The report points to the rising demand for generative AI tools, including OpenAI’s ChatGPT and Gemini, alongside Bytedance’s Doubao.

The EO directs the creation of an “AI Action Plan” within 180 days, led by the Assistant to the President for Science and Technology, the White House AI and Crypto Czar, and the National Security Advisor. Michael Kritsios (former US CTO under the Trump administration), David Sacks (venture capitalist and former PayPal executive), and US Rep. Mike Waltz (R-FL), have been nominated or appointed, respectively, to these positions. The revocation of the 2023 Eo shifts federal oversight from mandates to voluntary commitments, reducing requirements such as safety training submissions and large-scale computer acquisition notices, enabling less regulated innovation.

But one eye-opening slide shows who is adopting AI tools in game development—and for the most part, it’s not the people programming or creating assets for games. The heaviest AI use showed up for those working in «Business & Finance,» at 50 percent of respondents. Next up were those in «Production & Team Leadership» and «Community, Marketing, & PR» at 40 percent of respondents each.

• What strikes me as most alarming, however, is how this flurry of excitement around the agentic future has outpaced any sense of the industry’s present.
• A lawsuit in California accuses Linkedin of using private messages on its platform to train AI models, according to the BBC.
• In the Q1 survey, 28% of respondents cited it as a barrier, but in this Q4 survey, that figure climbed 10 percentage points to 38%.
• This issue is a barrier to broader AI adoption, highlighting the need for AI companies to develop solutions tailored to the specific regulatory and security requirements of the financial industry.
• The technology is also used to enhance virtual teaching with real-time instructor feedback and support.
• In their report, the researchers emphasize that Gen AI itself can also contribute to reducing the CO2 footprint of companies.

This not only undermines the reliability of AI-generated content but also poses significant risks when such content is used for critical security applications. Moreover, generative AI’s ability to simulate various scenarios is critical in developing robust defenses against both known and emerging threats. By automating routine security tasks, it frees cybersecurity teams to tackle more complex challenges, optimizing resource allocation [3]. Generative AI also provides advanced training environments by offering realistic and dynamic scenarios, which enhance the decision-making skills of IT security professionals [3]. Security firms worldwide have successfully implemented generative AI to create effective cybersecurity strategies.

AI revolution drives demand for specialized chips, reshaping global markets

Generative AI technologies are transforming the field of cybersecurity by providing sophisticated tools for threat detection and analysis. These technologies often rely on models such as generative adversarial networks (GANs) and artificial neural networks (ANNs), which have shown considerable success in identifying and responding to cyber threats. For talent coaches, the engine customizes employee career paths based on stored data, tracks their optimal career trajectory and matches staff to appropriate learning programs. GenAI tools make reports more comprehensive for all stakeholders, and users can query the bots for clarification when needed. Over the past three years, generative AI has transformed industries by creating new content in text, image, music and video formats. Derivatives of GenAI include chatbots, high-quality content, automated summarization, intelligent recommendation engines, virtual tutors and AI-powered creativity tools.

• It’s rare to see a week pass where we don’t hear about job losses in some form, but even so, that one in ten figure hits especially hard.
• At the center of Llama Stack’s design is its commitment to providing a consistent and versatile developer experience.
• But one eye-opening slide shows who is adopting AI tools in game development—and for the most part, it’s not the people programming or creating assets for games.
• With a keen interest in solving practical problems, he brings a fresh perspective to the intersection of AI and real-life solutions.
• By making this model open to everyone, DeepSeek is helping developers and businesses use advanced AI tools without needing to create their own from scratch.

The AI maker of ChatGPT, OpenAI, had scanned the Internet widely and used the various data on the Internet to establish patterns of how people write and describe things. In there, certainly, there would be plenty of content about physics and how physical objects in the real world move and act. In their report, the researchers emphasize that Gen AI itself can also contribute to reducing the CO2 footprint of companies. For example, the technology can be used to automate back-office tasks or to organize delivery routes or production processes more efficiently. These improvements would then require less energy to be used and would reduce CO2 emissions. Generative AI has the potential to accomplish a wide range of tasks, but there are challenges to its adoption.

The future of generative AI in combating cybersecurity threats looks promising due to its potential to revolutionize threat detection and response mechanisms. As organizations continue to leverage deep learning models, generative AI is expected to enhance the simulation of advanced attack scenarios, which is crucial for testing and fortifying security systems against both known and emerging threats [3]. This technology not only aids in identifying and neutralizing cyber threats more efficiently but also automates routine security tasks, allowing cybersecurity professionals to concentrate on more complex challenges [3]. As participants on a 2023 Deloitte panel observed, actors in government and public service sectors are increasingly using generative AI to build connections among people, systems and different government agencies. Use cases include content generation, proposal writing, planning, detection and data visualization. For example, the GenAI-powered tool BlueDot alerts public bodies to outbreaks or potential threats from new or known pathogens, such as influenza and dengue.

The AI Tutor, when toggled on by the professor, is embedded into STEM courses to support student learning. New data from Macmillan Learning finds AI tutors can assist in student learning and skill-building, as well as increase learner confidence to ask questions and dig deeper into materials. “The better those tools get… you could get to a place where they’re better than a direct human interaction,” she said.

Deutsche Bank leverages generative AI for software creation and managing adverse media, while the European neobank Bunq applies it to detect fraud. The future of artificial intelligence (AI) in banking is brighter than ever, as the adoption of AI-based solutions continues to gain pace. The potential for value creation for the financial services sector is immense, as AI could unlock an estimated $1 trillion of incremental value for banks annually, according to calculations by McKinsey & Co.

Without adequate equipment, sufficient staff, and financial assets, female candidates can fall behind their male counterparts. For less-resourced campaigners, GenAI tools can easily (and inexpensively) create promotional content. When used creatively, GenAI can allow female candidates to get their message out when more traditional options are cost prohibitive. Looking back at this past year of elections, IRI’s Technology and Democracy (TechDem) Practice has identified early impacts which shed light on how generative Artificial Intelligence (GenAI) may shape democracies in the future. IRI has found that it presents both benefits and harms to political actors, especially those from groups that may be disadvantaged. In particular, the experiences of women in the public sphere provide unique insight into GenAI’s advantages and drawbacks.