South Korea issues worlds first generative AI medical device guideline

Developers still aren’t warming up to generative AI

Setting up any public-facing content-producing project meant to communicate information to large numbers of people should be a hard, categorical “no” until further notice. But when an LLM spits out a wrong answer for a million people, that’s a problem, especially in Apple’s case, where no doubt many users are just reading the summary instead of the whole story. Didn’t see that coming,” and now some two-digit percentage of those users are walking around believing misinformation.

AI in this case is useful in developing artificial but highly accurate patient data sets that simulate real-life situations. Generative AI is being used in training machine learning models, conducting diagnoses, and performing forecast analysis. Around two years ago, the world was inundated with news about how generative AI or large language models would revolutionize the world.

The technology optimizes food supply chains by plotting and analyzing variables such as transportation costs, spoilage rates and market demand, ensuring fresh produce reaches consumers faster and at reduced costs. When it comes to sustainable farming practices, GenAI uses its massive database to simulate historic and current farming practices, predicting long-term environmental impacts. For example, Boston-based food tech firm Motif FoodWorks uses generative AI to design and test its plant-based foods, considering factors such as regional taste preferences, dietary requirements and even seasonal availability of ingredients. According to McKinsey, generative AI could add $200 billion to $340 billion in annual value to banking, largely through increased productivity.

The panel will also discuss the thorny problem of hallucinations, the impact AI learning from learning from its own creations, steps being taken to ensure reliability and accuracy, and how to verify that AI is safe, secure and trustworthy. IBM believes open-source base models empower organizations to create specialized, data-infused models. To support this, IBM open sourced its Granite family of customizable SLMs, trained on transparent, filtered datasets.

Consequently, users dedicated nearly 7.7 billion hours to AI applications in 2024, while apps incorporating the term “AI” were downloaded 17 billion times within the year. Notably, ChatGPT achieved an impressive milestone of 50 million monthly active users—outpacing the growth rates of platforms like Temu, Disney+, and YouTube Music. According to the annual “State of Mobile” report from app intelligence provider Sensor Tower, which acquired Data.ai, interest in AI apps has surged over the past year. If this growth trajectory continues, AI apps could potentially break into the top 10 by consumer spending within a year, as noted by the firm. As shown in the response by ChatGPT, the method of figuring out what would happen once the rubber ball was let go consists of using the data training that the AI underwent when first being set up.

How generative AI is paving the way for transformative federal operations – FedScoop

How generative AI is paving the way for transformative federal operations.

Posted: Thu, 23 Jan 2025 20:30:44 GMT [source]

Additionally, it creates customized route itineraries to find the best routes and automatically adjusts speed to suit the topography. The system also answers incoming calls and syncs calendar meetings, among other functions. According to Deloitte research, 92% of U.S. developers are already using these AI coding tools, with 70% of developers citing benefits such as better overall quality, faster production time and quicker resolution. For organizations to stay relevant, they need to upskill, reskill and continually improve employee performance. GenAI assists talent managers in creating a unified talent lifecycle, enabling organizations to engage with and assess candidates and employees and helping recruits realize their potential and ultimately thrive within the organization.

In contrast, a GenAI-powered chatbot — drawing from the company’s entire wealth of knowledge — dialogues with customers in a humanlike, natural way. This typically makes interactions faster as well as more efficient, responsive and personalized. At the same time, the chatbot learns from user feedback, improving its responses and minimizing its hallucinations and mistakes. Manually extracting daily transaction data from financial documents, such as bank statements or investment reports, can take anywhere from a few minutes to 10 hours, depending on the number of transactions. Annual reports from a single financial institution could contain over 1,000 transactions. GenAI-powered accounting tools, such as DocuAI, also improve financial reporting by producing detailed forecasts, simulating various financial scenarios and generating insightful reports.

If the sustained growth in downloads and engagement is any indication, the answer could be yes. With innovations like generative AI becoming more integrated into everyday tools, the appeal of these apps is only set to increase. This indicates that while consumers may be spending less time streaming, they’re willing to pay for premium content.

Podcast: The 6 biggest tech trends for businesses in 2025

Such strategies are usually better as compared to manual-based strategies, thereby ensuring the concerned financial institution has a competitive advantage in the market. As per a recent survey, around 74% of Business executives claimed that using Generative AI completely revolutionised their approach towards the business operations. Generative AI’s capability of providing organisations with unprecedented opportunities across all fields, such as manufacturing, healthcare, finance, entertainment, and marketing. Generative AI improves farming and food production through its ability to customize crop breeds.

Each time a model is used, perhaps by an individual asking ChatGPT to summarize an email, the computing hardware that performs those operations consumes energy. Researchers have estimated that a ChatGPT query consumes about five times more electricity than a simple web search. The power needed to train and deploy a model like OpenAI’s GPT-3 is difficult to ascertain.

This proactive approach significantly reduces the risk of breaches and minimizes the impact of those that do occur, providing detailed insights into threat vectors and attack strategies [3]. Leah Zitter, Ph.D., is a seasoned writer and researcher on generative AI, drawing on over a decade of experience in emerging technologies to deliver insights on innovation, applications and industry trends. On a bolder scale, a radio station in Poland replaced all its journalists with AI presenters but quickly abandoned the so-called experiment weeks later in the face of listener backlash. The Washington Post uses its GenAI-powered Heliograf tool to automate simple news stories on sports or election results. India Today employs AI news anchors, and Reuters built its own AI-assisted LLM to support clients with legal research.

If this growth trend continues, AI apps could soon join the ranks of the top 10 categories for consumer spending, a major milestone that reflects their rapid adoption. OpenAI, in its blog post, said that a layered safety approach with safeguards for the model, system, and post-deployment processes is essential. AI agents introduce a new wave of safety challenges, with potential risks including misuse for bypassing system safeguards. OpenAI has unveiled “Operator,” a new AI agent designed to perform web-based tasks, offering potential productivity enhancements for enterprises. Industry layoffs have continued, to the point where one in 10 developers say they’ve lost their jobs in the past year.

Generative AI Technologies

So now when an AI crawler downloads the subtitle file it can’t distinguish real subtitles from the garbage placed into it. For automakers, generative AI aids in research and development, vehicle design, quality control, testing, validation and predictive maintenance. As panelists at Germany’s renowned IAA Mobility International Motor Show pointed out, generative AI can simulate various scenarios for safer, innovative designs and more energy-efficient systems. For example, Google has developed a new GenAI technique that lets shoppers virtually try on clothes to see how garments suit their skin tone and size. Other Google Shopping tools use GenAI to intelligently display the most relevant products, summarize key reviews, track the best prices, recommend complementary items and seamlessly complete the order.

This analysis of an innovative AI breakthrough is part of my ongoing Forbes column coverage on the latest in AI including identifying and explaining various impactful AI complexities (see the link here). For my coverage of how generative AI such as ChatGPT, Claude, Llama, Gemini, and other major AI is increasingly being connected to robotic arms and akin robotic capacities, see the link here. The majority of companies worldwide seem to not be very concerned with the environmental impact of generative AI (Gen AI), according to a new report from Capgemini.

How AI will shape work in 2025 — and what companies should do now

This shift highlights the need for professionals to adapt by focusing on skills that complement AI, such as creativity, strategic thinking, and complex problem-solving. Educational institutions and training programs must also evolve, emphasizing AI literacy and interdisciplinary competencies to prepare individuals for the changing job landscape. Whether that’s contacting a hiring manager directly or sliding into a recruiter’s DMs on LinkedIn, you can ask a tool such as Perplexity to create professional sounding messaging for you. Another functional highlight is that you can ask Robin questions about company benefits, pay scales and salary, as well as details about company culture to help you research what it might be like to work at the particular company you’re applying to. You can find it on job boards and company career pages, where you can tell it your skills, career aspirations, or preferred work location and through agentic AI.

For example, AI will likely help banks launch new products that address the pain points of their customers much more precisely than human-generated ideas, enabling them to bring these new products to market faster. Train, validate, tune and deploy generative AI, foundation models and machine learning capabilities with IBM watsonx.ai, a next-generation enterprise studio for AI builders. Concern about regulatory compliance has proven a top inhibitor to organizations developing and deploying gen AI tools and applications. 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%.

In 2024, 21 percent of game developers thought generative AI would have a “positive” impact on the video game industry. Banks have a wealth of great data to leverage, and the more forward-looking players are focusing on building their own architecture that uses open-source pre-trained LLMs. The multi-modal capabilities of these LLM-based solutions – text, audio, text-to-speech and speech-to-text – have the power to disrupt and improve conventional customer communications channels. Smaller players and large financial institutions working in areas where so-called ‘low-resource languages’ are prevalent don’t have to stay in the margins and can also take advantage of the latest breakthroughs, thanks to declining costs. Luckily, some institutions with the right engineering talent, including TBC, have been able to build their own AI infrastructure and use open-source pre-trained models to incorporate Gen AI into their products.

Artificial Intelligence (AI) has largely become the term used to generically describe a variety of related but different concepts, often wrapping together AI, Machine Learning (ML), and Generative AI as if they all relate to the same thing. This climate of layoff fatigue is paired with a growing apathy towards generative AI tools, often touted as the industry’s future. “Game development is supposed to be art and an expression of one’s imagination, not an AI-generated concept with no real thought process,” reads the quote from a respondent that leads the section on Generative AI tools. A majority of developers (52%) surveyed said they worked at a company that uses such tools. 16% of respondents said their company has a policy against using generative AI tools, compared to 9% where their use was mandated.

These advancements include creating simple summaries of security incidents, enhancing threat intelligence capabilities, and automatically responding to security threats[4]. Another case study focuses on the integration of generative AI into cybersecurity frameworks to improve the identification and prevention of cyber intrusions. This approach often involves the use of neural networks and supervised learning techniques, which are essential for training algorithms to recognize patterns indicative of cyber threats. However, the application of neural networks also introduces challenges, such as the need for explainability and control over algorithmic decisions[14][1]. Moreover, generative AI technologies can be exploited by cybercriminals to create sophisticated threats, such as malware and phishing scams, at an unprecedented scale[4].

• Among those running for office, GenAI has proven to be an invaluable asset rather than a potential liability.
• Users can ask for suggestions, such as “things to do with friends at night,” and receive tailored ideas like visiting a speakeasy or attending live music events.
• However, as technologies like Generative AI move forward and are adopted and integrated by industries, there will arise issues pertaining to ethics and environmental concerns.
• Industry commitments and consortia will advance AI safety and development to meet societal needs, independent of federal or state policies.

It has been estimated that, for each kilowatt hour of energy a data center consumes, it would need two liters of water for cooling, says Bashir. A second piece will investigate what experts are doing to reduce genAI’s carbon footprint and other impacts. The team acknowledge that these are early days in the creation of quantum AI, but they are piling up a mound of evidence not only of its advantages, but how to tap into those benefits, such as making AI more energy efficient and more sustainable.

With that in mind, companies must think about how they might be able to implement AI solutions sustainably and ethically. In addition, generative AI is revolutionising the insurance industry since firms are now capable of generating bespoke insurance policies for their clients. Through Generative AI, the risk and behaviour of the customers can be evaluated to come up with specific insurance solutions that will make customers satisfied and companies likely to avoid any losses due to claims. AI systems are able to develop very efficient trading algorithms based on past stock exchange data and market factors, calculated after simulating numerous market conditions.

A lawsuit in California accuses Linkedin of using private messages on its platform to train AI models, according to the BBC. Abbott pointed to the January release of DeepSeek-R1, an open-source model family with greatly reduced usage fees compared to ChatGPT, as a harbinger of cost reductions to come. JPMorgan Chase executives expect the bank’s LLM Suite and other AI capabilities to create $2 billion in value, President and COO Daniel Pinto said last fall. Tools that can help engineers refactor COBOL applications were, by Abbott’s estimation, 70% to 75% accurate a year ago. The success of banking rests on its ability to rapidly and reliably process millions of daily transactions at scale — an undertaking that inherently benefits from a combination of cloud and AI. “Generative AI is going to impact every function within a bank — every single part of the job,” Accenture Global Banking Lead Michael Abbott said.

With OpenAI’s release of GPT-4o in the summer of 2024, consumer interest surged, but the appeal of these apps extended well beyond the initial buzz. AI agents open doors for various industries, particularly those seeking to enhance efficiency and streamline workflows. Their ability to automate tasks such as data collection and interaction with web-based platforms offers significant value for businesses. PC development has skyrocketed, more studios are prioritizing game accessibility, unionization support holds steady, and Hollywood continues to see the value in adapting games for the big (and small) screen. Produce powerful AI solutions with user-friendly interfaces, workflows and access to industry-standard APIs and SDKs. The Drawing Assist app is a powerful tool that combines generative AI with intuitive design to enable users to create, refine, and transform images.

They do this largely by regurgitating human creations like text, audio, and video into inferior simulacrums and, if you still want to exist on the Internet, there’s basically nothing you can do to prevent this sort of plagiarism. In a broader context, generative AI can enhance resource management within organizations. Over half of executives believe that generative AI aids in better allocation of resources, capacity, talent, or skills, which is essential for maintaining robust cybersecurity operations[4]. Despite its powerful capabilities, it’s crucial to employ generative AI to augment, rather than replace, human oversight, ensuring that its deployment aligns with ethical standards and company values [5].

“As you look at your long-term budget cycle, start investing in accelerated infrastructure so that you’ll be able to support the AI workloads that your customers and your employees are going to expect,” he says. In a new video interview for FedScoop, Department of Homeland Security Deputy CTO for AI & Emerging Technology Chris Kraft shared insights into DHS’s pioneering efforts with generative AI. “A lot of the work we’re doing now stems from our AI Task Force established in early 2023,” says Kraft. This task force laid the groundwork for initiatives like DHSChat, an internal AI tool supporting nearly DHS 19,000 employees, and three generative AI pilot programs.

AI is becoming an increasingly important factor of production in various industries and one of the most noticeable areas is the product designing domain. From inventory management to customer service, sales, store operations, loss prevention and beyond, GenAI has made retail operations exponentially easier and more effective. Manufacturing teams have to meet production goals across throughput, rate, quality, yield and safety. To achieve these goals, operators must ensure uninterrupted operation and prevent unexpected downtime, keeping their machines in perfect condition. However, navigating siloed data — such as maintenance records, equipment manuals and operating procedure documentation — is complicated, time-consuming and expensive. Microsoft’s news aggregator, MSN, attached an inappropriate AI-generated poll to a Guardianarticle about a woman’s death.

• The demand for generative AI is propelling global consumer spending on apps to $150 billion in 2024, a 13 percent increase from the previous year.
• In the realm of threat detection, generative AI models are capable of identifying patterns indicative of cyber threats such as malware, ransomware, or unusual network traffic, which might otherwise evade traditional detection systems [3].
• The report points to the rising demand for generative AI tools, including OpenAI’s ChatGPT and Gemini, alongside Bytedance’s Doubao.
• 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.

The gist is that AI is becoming further data-trained on how to cope with the physical world, the real world in which we all live. For example, the high-tech industry is responsible for the largest share of emissions on average, followed by life sciences and the utilities sector. Gen AI tools use enormous amounts of data and require far more data center capacity than traditional computing.