Agents

The authentic battle will be fought by ia agents

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The dispute over world supremacy that maintains US and China It permeates everything. The global economy, the most developed defense strategy, the commercial relationship between powers … and technology has an absolutely protagonist role in The delicate current geostrategic situation. Semiconductors and models of artificial intelligence (AI) are the resources used by the two countries with the greatest influence of the planet to measure its strength, and it is understandable that it is so. The range of applications in which the avant -garde and advanced AIs are crucial to guarantee the development of a country is very wide. Its scientific capacity, its industrial development, its economic competitiveness or its military power depend largely on these two resources. However, AIs are supported by semiconductors. Without integrated circuits of high density, high performance and high efficiency it is impossible to implement a really capable AI model. This is the reason why the US government is doing everything in your hand to prevent GPUs for avant -garde that design Nvidia, AMD, Intel or brains, among other companies, reach China. But for the moment the country led by Xi Jinping is resisting the pressure. Jensen Huang, the general director of Nvidia, has declared A few days ago, China is not behind in front of the US in AI. And the solvency of Deepseek, Ernie, Qwen, Pangu, Hunyuan or Sensenova endorses its analysis. The greatest growth potential is the AI ​​agents Right now it is very difficult to determine in an objective way which country leads in AI. It is reasonable to conclude that the US is ahead of China if we stick to the joint capacity and performance of its AI models, but the really relevant thing is to determine if that capacity entails a real value. This is The line of thought that defends experts As Arthur Lai, Chief of Research for Asia of the Macquarie Financial conglomerate, or Jason Corso, professor of AI at the University of Michigan (USA). The metrics that are currently used to evaluate the abilities and performance of the most advanced AI models are less and less clarifying In addition, it is important that we do not overlook that the metrics that are currently used to evaluate the abilities and performance of the most advanced AI models are less and less clarifying. And is that as The models improve and develop Its global competitiveness is equalized. During The Google I/O event last week the spokesmen of this American company said that Gemini is the fastest AI in the world because it reaches a speed of generation of Tokens ten times taller than Deepseek. An note before moving forward: the generation speed of Tokens It measures the speed with which a model of AI generates the answers, but it is only an indicator of the many that is necessary to use to evaluate the ability of an AI. Alibaba, on the other hand, assures that his last family of Qwen models surpasses his rivals if we stick to the ability with which he addresses mathematical reasoning or application programming. In this context, the most reasonable conclusion we can get is that each company affects those indicators that favor it. However, for users, the really important thing is the real value that an AI gives us. AND According to Lai, Corso and other experts The greatest growth potential has it AI agents and not so much the great language models themselves. An agent is an AI program that has been designed to make decisions for himself and behave in an autonomous way with the purpose of achieving a goal. The most important difference between an AI model and an AI agent is that the latter does not need us to tell him at every moment what he should do; Plan, analyze and execute tasks for yourself. This is the battlefield in which the companies that are dedicated to AI will compete, if they are not doing so. Image | Beyzaa Yurtkuran More information | Nikkei Asia In Xataka | The US wants to end the chips for the Chinese that are sold abroad. And China knows how to defend oneself

Agents are the great promise of AI. They also aim to become the new favorite weapon of cybercounts

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The AI ​​agents are not the future: they are here. While chatbots like Chatgpt either Gemini They continue to gain ground in tasks that range from solving daily doubts to help you in programming tasks, large technological ones have begun to take determined steps towards a new generation of much more promising systems. They are able to execute tasks, make decisions and adapt to the environment. They not only respond: they act. And that change is presented as a very powerful advance. OpenAi is developing Operatoran assistant who can navigate pages, book trips or manage files. Anthropic proves your own agent with similar functions in controlled environments. Google works in Jarvis, his future digital butler. The idea is clear: delegate real tasks in artificial intelligences. But that same autonomy that makes them useful allies also makes them a potential risk for cybersecurity. Dangerous autonomy. Unlike traditional bots, AI agents are not limited to predefined instructions. They can control an operating system or make decisions depending on the context. In wrong hands, this autonomy could facilitate complex attacks without the need for human experts. Some laboratory tests already show how these models can replicate operations that previously required advanced technical knowledgesuch as automating spying tasks or manipulating system configurations. The threat begins to appear. Although there is no evidence that they are involved in large -scale cyber attacks, signs have begun to appear. Platforms like LLM Agent Honeypot, designed to detect suspicious accesses, have registered interactions with possible AI agents. In two confirmed cases, the agents responded to instructions embedded with a typical speed of language models, which points to their growing sophistication. We do not talk about organized offensives yet, but of an increasingly real phase. Cheaper, faster, more scalable. As Mit Technology Review points outone of the biggest risks is the potential for climbing. An agent can execute automated actions hundreds of times by a fraction of the cost of a human team. For criminals, that means expanding operations with unprecedented efficiency. If today the mass attacks require investment and specialized personnel, tomorrow they could be launched automatically, selecting objectives and exploring vulnerabilities without constant supervision. LLM Agent Honeypot operation operation scheme Detecting them is not so easy. Although current cybersecurity tools are effective against sophisticated threats, agents introduce a new type of challenge. Unlike classic malware, these systems can reason, adapt to the environment and modify their real -time behavior. This ability to mimic with legitimate traffic forces to rethink detection methods and to develop specific techniques to identify patterns of artificial intelligence. The industry is still exploring how far these systems can go. Some investigations show that, given ambiguous instructions, certain agents can execute unexpected actions. Although they still need human support to complete complex attacks, their evolution is rapid. And the most disturbing is not what they can do today, but what they could do tomorrow. And they will do it in an increasingly adverse scenario. According to checkpoint datain the third quarter of 2024, cyber attacks increased 75% compared to the same period of the previous year. Each organization suffered on average 1,876 weekly attacks. Sectors such as education, government or health are among the most beaten, and regions such as Africa, Europe and Latin America registered alarming growth. The hardware industry, for example, saw the attacks grow by 191% in just one year. More than 1,200 ransomware incidents were reported only in that quarter, mainly affecting manufacturers, hospitals and public administrations. If these types of attacks are delegated to AI agents capable of selecting objectives and launching chain offensives, the impact could be shot. The global panorama is tense, and the agents could be the multiplier that the attackers were waiting. Images | Xataka with chatgpt | Palisade Research In Xataka | There is a person who knows more than anyone in the world about password robberies. And they just steal his

Openai’s new voice models already speak as customer service agents. His next destination: the call centers

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Since the beginning of the year, the objective of great technological ones has been clear: that we talk to artificial intelligence (ia). Openai, Microsoft, Google and Meta have added voice functions to their assistants. But this seems to be just the beginning. The industry advances at a frantic pace and the way we interact with these tools continues to evolve. Tell the voice agents ‘hello’. Sam Altman’s company has been betting on text agents with tools such as Operator either Computer-Useing agents. However, Openai already has it ready if next great movement to continue highlighting in the race for the development of AI: to promote a new and powerful generation of voice agents. New models on stage. OpenAI has announced The launch of new audio models to turn voice into text and vice versa. They are not in chatgpt, but in the APIwhere developers can use them to create voice agents. The important thing? They aim to be much more precise and to bring customization to the next level. The new OpenAI models, built on GPT-4O and GPT-4O-minipromise to improve Whisper Already its previous text to voice tools, which will also remain active through the API. But it is not just a matter of performance: now they can also modulate their tone to sound, for example, “as an empathic customer service agent.” Destination: the call centers. Openai makes it clear where they point with this launch. He assures that “for the first time, developers can tell the model not only to say, but also how to say it, which allows more personalized experiences for use cases ranging from customer service to creative narrative.” According to Openai, this technology will allow creating much richer “conversational experiences.” If we take into account that Chatgptpowered by GPT-3.5arrived in November 2022, it is evident that the progress has been vertiginous. And everything indicates that these models will end up arriving at the call centers. We might think that at first the interactions will be somewhat limited, but well above the current voice systems. They will move away from traditional automated assistants and will be much more natural. Over time, the line between a conversation with a person and an AI could become almost imperceptible. Images | Charanjeet Dhiman | OpenAI In Xataka | We have tried Sesame’s conversational. It is the experience closest to a “human voice” that we have seen In Xataka | China has found an unusual strategy to avoid US mosquadillas with AI: bet on the Open Source

AI agents are promising. But as in Tesla’s FSD, you better not take your hands from the steering wheel

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AI agents are one of the great trends of AI This year. There are many expectations put in these models of AI capable of completing a task from beginning to end for us and almost if our intervention. And yet, one thing seems clear: for the moment it will be better “not to remove your hands from the steering wheel” and watch every step they take to prevent the AI ​​agent from being starring. Autonomy and trust. The Tesla driving assistance system –badly called Total autonomous driving (FSD For its acronym in English) – it requires that the user trust him to get carried away and that the car takes us from a point of origin to a destination without human intervention. IA agents propose a similar idea, to complete a task from beginning to end autonomously, but for this we must trust that they are able to do so. decision making. The agents will require huge data amounts and access to updated sources of information to analyze such data and then make decisions. In the past we have seen how AI models are especially good at the time of Summarize concrete information Or to draw conclusions from limited data, which is very useful for that decision making. Learn from mistakes. Tesla cars receive FSD frequent updates to improve their behavior. These updates are nourished by the data collected by the company when your FSD system is used, what allows you to polish the service. Something similar is expected to happen with AI agents, which will improve – especially at the beginning – when they are updated and “learn from their mistakes” when processing user requests. AI and companies agents. These types of solutions will be especially striking in companies that can thus automate processes that previously required total or partial human intervention. And precisely that is why this type of integration must be done in a very controlled way, because let’s admit it: we cannot trust 100% of the current AI models. Tesla knows that FSD is imperfect. It happens of course in the FSD of Tesla, which since its inception has been involved in various accidents, some of them with fatalities. One of the most recent was notified in October 2024: the low visibility made a TESLA with FSD activated a few months ago will run a pedestrian. Tesla has been criticized on numerous occasions of misleading advertising and of save the maximum on radars and sensors To achieve greater profit margin. AI agents can be equally dangerous if they are used incorrectly and “without having their hands in the steering wheel.” Users and companies that begin to use them must keep these risks very present. The hands behind the wheel, please. The conclusion was already clear in the Tesla FSD system, but also in the case of agents. They have barely done only appear on the market shyly, but everything indicates that this is one of the great trends of AI by 2025. And the problem is that the models of AI are imperfect and therefore can make mistakes, but it is that in the agents of that error it will increase. That they tell Air Canada, who had to return money to a passenger which obtained an erroneous response from the airline chatbot. Or to Chevrolet, whose chatbot was “deceived” by a user who achieved Buy one of your cars for a dollar. Domino effect. The accumulation of errors in sequential tasks is a fundamental problem in current AI models. We could say that it is something like the domino effect or the compound error: an error in an initial action distorts all subsequent decisions, generating results increasingly far from what expected. Imagine that in applications such as finance, medicine or logistics: consequences could be terrible. Solution: Constant supervision. To avoid this problem there are several proposed solutions. One of them is the establishment of check points. Thus, at the end of each subtarte the system-and ideally, a human user, what is called Human-In-The-Loop (Hitl)-should verify that everything is going well. It is also possible to minimize the risk using redundant systems – for example, using different models of AI so that the AI ​​agent uses them separately – or taking advantage of the information of the standard limits: if an intermediate fact thrown by an AI agent is too diverted from what is expected, we should rebound that process. And for the moment, spent (very) bounded. We are in a preliminary phase, and AI agents are “learning to drive alone”, so to speak. And the best way they learn is to go step by step and always starting with relatively simple and very limited scenarios. Thus, the ideal is to try to apply them to very specific cases and with a limited and known casuistry, so that their answers are as precise. Image | Erik Witsoe In Xataka | Microsoft is very important that the agents of AI are the great ball of the year. And is being reorganized to achieve it

OpenAi already prepares agents of AI capable of replacing the most valuable employees. And plans to charge $ 20,000 per month for them

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Many feared that AI stole their work. However, new leaked data In The Information They raise a quite different situation, because the prices that OpenAi shuffles for their future advanced agents is absolutely extraordinary. $ 20,000 per month for an AI agent. According to this medium, Openai plans to launch several AI agents oriented to various tasks and scenarios. And the more advanced and specialized, the more expensive they will be. In fact, the most expensive they are talking about would be an investigating agent with the level of a human doctorate, and that would cost $ 20,000 per month. Hiring AI employees will not be cheap. There are other agents such as the qualified as a “knowledge worker with high income” that will have an estimated price of 2,000 dollars per month. If what we want is subtitUOpenai’s proposal will cost $ 10,000 per month. Agents who will work at all hours. The theoretical advantage of these agents is that they will be able to do a theoretically impeccable job, but they will also do it at all hours, without breaks or breaks, without weekends or vacations and without getting bad. If they are really able to do the job as well (or better) as a human being in that position, the investment may come out very profitable. There is no estimated date. It is not clear when these agricultural IAS will be launched or when they will be available for companies, but in The Information they point out how SoftBank – a versor in Openai – has committed to invest 3,000 million dollars in OpenAi agents this year. And OpenAi needs a lot of money. Those expensive subscriptions would leave the current Chatgpt Pro plan of 200 dollars a month, but are of course the road that OpenAi has to become profitable. Today, like most AI companies, OpenAi is burning money and spends much more than he enters. The Plan: Be profitable in 2029. Internal data were leaked months ago according to which OpenAI I hoped to be profitable in 2029. To achieve this they have a fairly simple plan: offer increasingly faces that will make users who want to access their most advanced AI models pay small fortunes monthly. The AI ​​revolution will face. If we listen to these new rumors, it will be better for companies to prepare for the future. One in which they may have the option of “hiring AI employees”, but They are better to be profitablebecause everything indicates that their salaries will be high. Image | Techcrunch In Xataka | “I have three years of work”: more and more IA managers believe that AI will end up removing the position

Operator works differently (and better) to other agents who see our screen. Your secret: Cu

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We already have OpenAi’s agent. It is called Operatorand it is a system capable of seeing our screen and performing actions autonomously in the browser from our requests. It is something we had already seen with ‘Computer Use’ from Anthropic either Deepmind Marinerbut here the company led by Sam Altman has its own special ingredient. Computer-Useing Agent (Cua). Operator uses a model called Computer-Useing Agent (CUA) that is based on GPT-4O. CUA interprets screenshots and interacts with websites through the typical browser controls, such as a cursor or a mouse. How Cua works. As they explain In Openai’s documentationthis system processes those “raw pixels” of the captures that you make and use a mouse and a virtual keyboard to complete its actions. Once you have the screenshot, “reason” and follow a “thought” line in which the past actions take into account. Promising performance. There are several benchmarks since they allow to evaluate the ability of these agricultural models. According to them tests performed internally In Openai, CUA achieves a 38.1% performance in OSWORLD (Use of a computer in general) against platforms such as Anthropic, which achieves 22%. Humans, yes, achieve 72.4% on average, which makes it clear that these systems still have a lot of improvement margin. In the use of the browser, the Benchmarks Webarena and Webvoyager also allow Operator to score very high: 58.1% and 87% respectively, compared to 36.2% and 56% of their competitors. What about those catches that I collect operator. Operator continuously performs screenshots to “see” the browser interface with which he interacts. That browser does not run on our PC, but in a remote browser on OpenAI servers. User data, including these catches, are used according to OpenAI’s privacy policy. This is: they can be used to detect fraudulent activities and to improve the service. That implies that our data can be used to train and improve the model, although We can deactivate that option In operator settings. The user, yes, has the capacity for how long this data is stored in Operator. By default these data are saved until the user decides to delete them. An agent who asks for help (and confirmation) when he needs them. As we have seen in other agents such as ‘Computer Use’ of Anthropic, Operator is an agent who does not act crazy. If you meet an obstacle – like a captcha code or the request to introduce user and password on a website – you will ask that the user take control, and will also ask for the final user confirmation if for example we have to validate a reservation or purchase of a product that has sought Operator. The operator user can also take control at all times. This is how it works. Source: OpenAi Do not release the steering wheel. This reminds us of assisted driving systems such as Tesla FSD. It is true that it is able to take us from one place to another once we introduce the destination address, but it is important to continue paying attention and have our hands in the steering wheel in case they occur unforeseen. With Operator and the rest of this type agents something similar happens. There are things that cannot be done. At the moment Operator cannot complete specialized tasks such as managing complex calendar systems or interacting with very personalized or non -standard websites. You will also refuse to do some tasks with high risk of provoking damages. For example, send emails, make electronic transactions or delete calendar events. Its benefits and capabilities will increase, without a doubt, but they will gradually do so and always guaranteeing that the possibility of error is the least possible. Image | OpenAI In Xataka | The generative AI seems stagnant. Big tech believe they have an ace in the sleeve: “agents” who do things for us

ChatGPT: What are the Autonomous Agents presented by OpenAI?

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OpenAI announced this Thursday the launch of “Operator”an artificial intelligence agent designed to perform tasks on the web autonomously. This tool is available in preview for ChatGPT Pro subscribers in the United States, with a monthly cost of $200. What is Operator? Operator is a artificial intelligence agent which combines the vision capabilities of GPT-4o with advanced reasoning obtained through reinforcement learning. This integration allows Operator to interact with web pages using screenshots and perform actions such as typing, clicking and scrolling through the content. Unlike traditional chatbots, Operator can execute complex tasks autonomouslysuch as shopping for groceries, filing expense reports, making restaurant reservations, and managing corporate data. Operator Capabilities – Autonomous web interaction: Operator can browse websites, fill out forms, and perform online actions without direct human intervention. Its ability to interpret and manipulate web interfaces allows you to automate tasks that previously required manual interaction. – Correction and security: The agent is designed to self-correct and request user intervention when faced with sensitive information or critical actions, thus ensuring safe and reliable use. – Strategic collaborations: OpenAI is working with companies like DoorDash, Instacart and Uber to ensure that Operator meets real market needs, expanding its applicability in various sectors. Significant advance in artificial intelligence The introduction of Operator represents an important step in the evolution of artificial intelligence, marking the transition from simple chatbots to more autonomous agents capable of performing complex tasks. This development has the potential to transform efficiency in the workplace, allowing virtual employees to integrate into the workforce in the near future. Besides, OpenAI anticipates that by 2025, AI-powered assistants that can reason and carry out complex tasks on behalf of users will become commonplace. This advancement not only improves individual productivity, but also has significant implications for various industries seeking to automate routine processes and free up time for more strategic activities. Challenges and considerations Despite Operator’s promising capabilities, there are challenges in its implementation. Some complex web interfaces may present difficulties for autonomous agent interaction. Additionally, although Operator is designed with built-in security features and requests approvals for high-risk tasks, it does not yet handle banking transactions or job application decisions, indicating the need for continuous human oversight in certain contexts. OpenAI’s launch of Operator marks a milestone in the development of autonomous AI agents, offering a powerful tool to automate web tasks and improve efficiency across multiple domains. Keep reading:• OpenAI prepares a new AI for January and this is what we know• OpenAI presented Sora, the AI ​​capable of generating hyperrealistic videos in seconds• OpenAI CEO revealed that the company is losing money for a very peculiar reason

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