Pax Silica is a United States-led international initiative focused on strengthening and coordinating "trusted" supply chains for advanced technologies—especially semiconductors, artificial intelligence (AI) infrastructure, critical minerals, advanced manufacturing, logistics, and associated energy and data infrastructure. The initiative is coordinated by the US Department of State and was launched in December 2025 alongside the signing of the non-binding Pax Silica Declaration by an initial group of partner countries. The initiative describes itself as a "positive-sum" partnership intended to reduce "coercive dependencies" and improve resilience across the full technology stack, from mineral extraction and processing through chip manufacturing and computing infrastructure. US officials described Pax Silica as a framework for coordinating flagship projects and policy alignment across partner countries, including supply-chain mapping, investment and co-investment initiatives, and protection of critical infrastructure and sensitive technologies. Reuters reported discussions of projects linked to trade and logistics routes and an industrial park initiative in Israel. Gulf countries, such as the UAE and Qatar, are betting on attracting AI companies with cheap energy. Moreover, the UAE's potential to invest in Pax Silica's activities has been noted as a fundamental asset for the initiative. In early 2026, the U.S. announced plans to contribute $250M toward an investmest consortium that's intended to strengthen energy and critical mineral supply chains. == Launch and background == During the 2020s, governments increasingly treated supply-chain resilience in semiconductors, critical minerals, and AI-related computing infrastructure as a national-security priority, amid export controls, industrial policy measures, and geopolitical competition over the technologies underpinning advanced manufacturing and AI. Pax Silica was presented by US officials as an economic-security framework aimed at aligning policies and investment among "trusted partners" that host major technology firms and key industrial capacity. Pacific Forum's analyst Akhil Ramesh, writing for the National Interest magazine, described the initiative as understanding that: "economic security today is inseparable from control over energy, critical minerals, high-end manufacturing, and advanced models." On December 11, 2025, the US Department of State announced the inaugural Pax Silica Summit and a planned signing of the Pax Silica Declaration, describing Pax Silica as the Department's flagship effort on AI and supply-chain security. The initial summit was held in Washington, D.C. on December 12, 2025. The State Department fact sheet described cooperation areas including connectivity and data infrastructure, compute and semiconductors, advanced manufacturing, logistics, mineral refining and processing, and energy. == Membership == Pax Silica participation has been discussed in terms of (1) countries that have signed the declaration and (2) countries invited to summit discussions or publicly reported as prospective signatories but which had not (as of mid-January 2026) signed the declaration. === Countries that signed the Pax Silica Declaration === Seven countries signed the declaration at the December 12, 2025, summit in Washington, D.C.: Australia Israel Japan South Korea Singapore United Kingdom United States Some countries who attended the initial conversations did not immediately sign, while additional countries were invited to join after the discussions concluded. The following are the later signatory countries on the declaration: Greece Netherlands (joined December 17, 2025; "non-signing partner") Qatar (joined January 13, 2026) United Arab Emirates (joined January 14, 2026) India (joined February 20, 2026) Sweden (signed March 17, 2026) Finland (signed April 16, 2026) Philippines (signed April 17, 2026) Norway (signed May 6, 2026) === Countries invited / participating, but not yet signed === At launch, US materials and contemporaneous reporting described additional invited participants and observers, including: Canada – observer/participant in related discussions, per US briefing materials; not listed among signatories. Taiwan – participated in summit sessions according to a State Department briefing; not listed among signatories. The Organisation for Economic Co-operation and Development (OECD) and European Union were also noted by US officials as present in an observer capacity, but are not countries.
NER model
NER is one of several formulas for accessing live subtitles in television broadcasts and events that are produced using speech recognition. The three letters stand for number, edit error and recognition error. It has been promoted as an alternative to Word error rate (Word Error Rate) which is a more objective measure. The overall score is calculated as follows: Firstly, the number of edit and recognition errors is deducted from the total number of words in the live subtitles. This number is then divided by the total number of words in the live subtitles and finally multiplied by one hundred. N E R v a l u e = N − E − R N ∗ 100 {\displaystyle NERvalue={\frac {N-E-R}{N}}100} . The acronyms stand for the following: N (number) = total number of words in the live subtitles E (Edit error) = edit error R (Recognition error) = recognition error This measurement process has been used for public television broadcasts in European countries like Italy and Switzerland. One major drawback with NER is that it requires a human assessor to rate errors as either: 1 Minor edition or recognition errors 2 Normal edition or recognition errors 3 Serious errors which are then weighted in the assessment process. This is both subjective, time consuming and costly. Also, NER fails to account for words left out subtitles which is something that does not take account of the D/deaf audience who want verbatim subtitles. As a result, NER cannot accurately reflect the audience's experience of subtitles. Another problem is the inconsistency of human evaluation of subtitles, particularly with live subtitles, where there are differing opinions of the importance of subtitle errors. By way of contrast, Word error rate is an objective measure of subtitle errors, since it measures the textual discrepancy between the subtitles and the speech.
Agent Communications Language
Agent Communication Language (ACL) consists of computer communication protocols that are intended for AI agents to communicate with each other. In 2007, protocols of this nature were proposed which include: FIPA-ACL (by the Foundation for Intelligent Physical Agents, a standardization consortium) KQML (Knowledge Query and Manipulation Language) After the surge in Generative AI with the use of Transformers and Large language models, the definition of agent has shifted away from physical agents to signify software systems built using the principles of Agentic AI. A new protocol to emerge in this area is Natural Language Interaction Protocol (NLIP). NLIP is an application-level communication protocol defined between AI Agents or between a human and an AI agent. Ecma International; a standards body which develops and publishes international standards for the information and communication industry; published on 10 December 2025 five new standards and one technical report defining the Natural Language Interaction Protocol (NLIP). As a result, we can define agent communication protocols into two categories: ontology based agent communication protocols and generative AI based agent communication protocols. Ontology based agent communication protocols use a common ontology to be used between agents. An ontology is a part of the agent's knowledge base that describes what kind of things an agent can deal with and how they are related to each other. FIPA-ACL and KQML are examples of such protocols. These protocols rely on speech act theory developed by Searle in the 1960s and enhanced by Winograd and Flores in the 1970s. They define a set of performatives, also called Communicative Acts, and their meaning (e.g. ask-one). The content of the performative is not standardized, but varies from system to system. Implementation support of FIPA-ACL is included in FIPA-OS and Jade. Generative AI based agent communication protocols such as NLIP do not require a shared ontology among communicating agents. In its stead, they use generative AI models to translate natural language text, images, videos or other modalities of data into a local ontology. This provides for hot-extensibility where the same protocol can be used for multiple communication needs, and simplifies version control since different agents can use different versions of a shared ontology. NLIP has been designed with security considerations in mind. The specification and standards comprising NLIP are developed and maintained by Ecma Technical Community 56.
OpenClaw
OpenClaw is a free and open-source autonomous artificial intelligence agent that can execute tasks via large language models (LLMs), using messaging platforms as its main user interface. == History == Developed by Austrian agentic engineer Peter Steinberger, OpenClaw was first published in November 2025 under the name Warelay. The software was derived from Clawd (now Molty), an AI-based virtual assistant that he had developed, which itself was named after Anthropic's chatbot Claude. Within two months it was renamed twice: first to "Moltbot" (keeping with a lobster theme) on January 27, 2026, following trademark complaints by Anthropic, and then three days later to "OpenClaw" because Steinberger found that the name Moltbot "never quite rolled off the tongue." At the same time as the first rebranding, entrepreneur Matt Schlicht launched Moltbook—a social networking service which was intended to be used by AI agents such as OpenClaw. The viral popularity of Moltbook coincided with an increase in interest in the project, with the open-source project having 247,000 stars and 47,700 forks on GitHub as of March 2, 2026. Chinese developers adapted OpenClaw to work with the DeepSeek model and domestic messaging super apps such as WeChat, while companies such as Tencent and Z.ai announced OpenClaw-based services. On February 14, 2026, Steinberger announced he would be joining OpenAI, and that a non-profit foundation named OpenClaw Foundation would be established to provide future stewardship of the project. == Functionality == Steinberger describes OpenClaw as being an AI-based virtual assistant, serving as an agentic interface for autonomous workflows across supported services. OpenClaw bots run locally and are designed to integrate with an external large language model such as Claude, DeepSeek, or one of OpenAI's GPT models. Its functionality is accessed via a chatbot within a messaging service, such as Signal, Telegram, Discord, or WhatsApp. Configuration data and interaction history are stored locally, enabling persistent and adaptive behavior across sessions. OpenClaw uses a skills system in which skills are stored as directories containing a SKILL.md file with metadata and instructions for tool usage. Skills can be bundled with the software, installed globally, or stored in a workspace, with workspace skills taking precedence. OpenClaw has seen adoption among small businesses and freelancers for automating lead generation workflows, including prospect research, website auditing, and CRM integration. == Security and privacy == OpenClaw's design has drawn scrutiny from cybersecurity researchers and technology journalists due to the broad permissions it requires to function effectively. Because the software can access email accounts, calendars, messaging platforms, and other sensitive services, misconfigured or exposed instances present security and privacy risks. The agent is also susceptible to prompt injection attacks, in which harmful instructions are embedded in the data with the intent of getting the LLM to interpret them as legitimate user instructions. Cisco's AI security research team tested a third-party OpenClaw skill and found it performed data exfiltration and prompt injection without user awareness, noting that the skill repository lacked adequate vetting to prevent malicious submissions. One of OpenClaw's own maintainers, known as Shadow, warned on Discord that "if you can't understand how to run a command line, this is far too dangerous of a project for you to use safely." In March 2026, Chinese authorities restricted state-run enterprises and government agencies from running OpenClaw AI apps on office computers in order to defuse potential security risks. === MoltMatch dating-profile incident === In February 2026, news coverage highlighted a consent-related incident involving OpenClaw and MoltMatch, an experimental dating platform where AI agents can create profiles and interact on behalf of human users. In one reported case, computer science student Jack Luo said he configured his OpenClaw agent to explore its capabilities and connect to agent-oriented platforms such as Moltbook; he later discovered the agent had created a MoltMatch profile and was screening potential matches without his explicit direction. Luo said the AI-generated profile did not reflect him authentically. The same reporting described broader ethical and safety concerns around agent-operated dating services, including impersonation risks. An AFP analysis of prominent MoltMatch profiles cited at least one instance where photos of a Malaysian model were used to create a profile without her consent. Commentators cited in the reports argued that autonomous agents can make it difficult to determine responsibility when systems act beyond a user's intent, particularly when agents are granted broad access and authority across services. == Reception == A review in Platformer cited OpenClaw's flexibility and open-source licensing as strengths while cautioning that its complexity and security risks limit its suitability for casual users. Technology commentary has linked OpenClaw to a broader trend toward autonomous AI systems that act independently rather than merely responding to user prompts. In March 2026, the Chinese government moved to restrict state agencies, state-owned enterprises, and banks from using OpenClaw, citing security concerns, such as unauthorised data deletion and leaks, and excessive energy usage. While regulators warn of potential security risk associated with using OpenClaw, local governments in several tech and manufacturing hubs have announced measures to build an industry around it. Rival companies developed related products. Although Microsoft CEO Satya Nadella described OpenClaw in February 2026 as a "virus"-like security risk, by May 2026 the company's "Project Lobster" was internally testing "ClawPilot", an OpenClaw-based desktop environment. By then Google was building "Remy", its own agent. Despite the Chinese government's warnings against OpenClaw, Chinese investors searched for other companies that might benefit from the "lobster trade", . == Community and ecosystem == OpenClaw's open-source model has fostered a growing ecosystem of third-party tools, deployment services, and content platforms. Chinese technology companies including Tencent and Z.ai announced OpenClaw-based services, while developers adapted the software for domestic models and messaging apps such as WeChat. Independent creators have built deployment guides, skill directories, and use-case collections around the framework. The project's extensible skills system has attracted both community contributions and security scrutiny, with researchers noting risks in unvetted third-party skills.
User profile
A user profile is a collection of settings and information associated with a user. It contains critical information that is used to identify an individual, such as their name, age, portrait photograph and individual characteristics such as knowledge or expertise. User profiles are most commonly present on social media websites such as Facebook, Instagram, and LinkedIn; and serve as voluntary digital identity of an individual, highlighting their key features and traits. In personal computing and operating systems, user profiles serve to categorise files, settings, and documents by individual user environments, known as 'accounts', allowing the operating system to be more friendly and catered to the user. Physical user profiles serve as identity documents such as passports, driving licenses and legal documents that are used to identify an individual under the legal system. A user profile can also be considered as the computer representation of a user model. A user model is a (data) structure that is used to capture certain characteristics about an individual user, and the process of obtaining the user profile is called user modeling or profiling. == Origin == The origin of user profiles can be traced to the origin of the passport, an identity document (ID) made mandatory in 1920, after World War I following negotiations at the League of Nations. The passport served as an official government record of an individual. Consequently, Immigration Act of 1924 was established to identify an individual's country of origin. In the 21st century, passports have now become a highly sought-after commodity as it is widely accepted as a source of verifying an individual's identity under the legal system. With the advent of digital revolution and social media websites, user profiles have transitioned to an organised group of data describing the interaction between a user and a system. Social media sites like Instagram allow individuals to create profiles that are representative of their desired personality and image. Filling all fields of profile information may not be necessary to create a meaningful self-presentation, which grants individual more control over of the identity they wish to present by displaying the most meaningful attributes. A personal user profile is a key aspect of an individual's social networking experience, around which his/her public identity is built. == Types of user profiles == A user profile can be of any format if it contains information, settings and/or characteristics specific to an individual. Most popular user profiles include those on photo and video sharing websites such as Facebook and Instagram, accounts on operating systems, such as those on Windows and MacOS and physical documents such as passports and driving licenses. === Social media === Effectively structured user profiles on social media channels such as Instagram and Facebook offer a way for people to form impressions about someone that is predictive or similarly meeting them offline. The condensed format of social media profiles allows for quick filtering of millions of profiles by matching individuals by similar characteristics and interests; information provided upon sign up. A research conducted highlights that only a "thin slice" of information is required to form an impression about an individual online (Stecher and Counts 2008). Online user profiles eliminate the complexity of interaction that is present in 'face-to-face' meetings such as behavioural, facial, and environmental information, resulting in increased predictiveness of user personality. Dating apps and websites solely rely on an individual's user profile and the information provided to form interactions and communication with others on the platform. Despite having control over presented information, lying is minimal in online dating contexts (Hancock, Toma and Ellison, 2007). Apps such as Bumble allow users to 'match' with other individuals based on their characteristics and selected filters that allow users to narrow the spectrum of search to their preference. Information for a user's profile is voluntarily specified by the user and includes information such as height, interests, photographs, gender or education. The requirement of information varies respective to each platform, and there surrounds little consensus to an appropriate amount of information for a condensed user profile. Universally, all social networking platforms display an individual's profile picture and an "about me" page that allows for self-expression. === Influencers === Influencer user profiles are third party endorsers who shape audience attitudes and decisions through social media content such as photos, blogs and tweets. Social Media Influencers (SMI) often hold a significant following on a social media platform which enables them to be recognised as opinion leaders to shape an information influence to their audience. 'Influencer marketing' industry gained prominence in 2018, when the photo sharing app Instagram crossed 1 billion users, subsequently with approximately 60,000 google search queries for 'influencer marketing' the same year. Influencer user profiles hold a unique selling point, or public personality that is unique and charismatic to the needs and wants of their target audience. SMI profiles advertise product information, latest promotions and regularly engage with their followers to maintain their online persona. Messages endorsed by social media influencers are often perceived as reliable and compelling, as a study conducted found 82% of followers were more inclined to follow the suggestions of their favorite influencer. This allows advertisers to leverage online user profiles and their audience rapport to target younger and niche audiences. According to a market survey, influencer marketing through social media profiles yields a return 11 times higher than traditional marketing, as they are more capable of communicating to a niche segment. Most popular influencers include sport starts such as Cristiano Ronaldo and Hollywood personalities such as Dwayne Johnson and Kylie Jenner each with over 200 million followers respectively. === Ecommerce === Online shopping or Ecommerce websites such as Amazon use information from a customer's user profile and interests to generate a list of recommended items to shop. Recommendation algorithms analyse user demographic data, history, and favourite artists to compile suggestions. The store rapidly adapts to changing user needs and preferences, with generation of real time results required within half of a second. New profiles naturally have limited information for algorithms to analyse, and customer data of each interaction provides valuable information which is stored as a database linked with each individual profile. User profiles on ecommerce websites also serve to improve sales of sellers as individuals are recommend products that other "customers who bought this item also bought" to widen the selection of the buyer. A study conducted found that user profiles and recommendation algorithms have significant impact on related product sales and overall spending of an individual. A process known as "collaborative filtering" tries to analyse common products of interest for an individual on the basis of views expressed by other similar behaving profiles. Features such as product ratings, seller ratings and comments allow individual user profiles to contribute to recommendation algorithms, eliminate adverse selection and contribute to shaping an online marketplace adhering to Amazons zero tolerance policy for misleading products. == Digital user profiles == Modern software and applications account for user profiles as a foundation on which a usable application is built. The structure and layout of an application such as its menus, features and controls are often derived from user's selected settings and preferences. The origin of digital user profiles in computer systems was first initiated by Windows NT that held user settings and information in a separate environment variable named %USERPROFILE% and held the framework to a user's profile root. Consequently, operating systems such as MacOS further accelerated prominence of user profiles in Mac OS X 10.0. Iterations since have been made with each operating system release with the aim to maximise user friendliness with the system. Features such as keyboard layouts, time zones, measurement units, synchronisation of different services and privacy preferences are made available during the setup of a user account on the computer === Types of accounts === ==== Administrator ==== Administrator user profiles have complete access to the system and its permissions. It is often the first user profile on a system by design, and is what allows other accounts to be created. However, since the administrator account has no restrictions, they are highly vulnerable to malware and viruses, with potential to impact all other accounts.
CapCut
CapCut, known domestically as JianYing (Chinese: 剪映; pinyin: Jiǎnyìng) and formerly internationally as ViaMaker, is a video editor developed by ByteDance, available as a mobile app, desktop app, and web app. == History == The app was first released in China in 2019 and was initially available for iPhone and Android. In 2020, it was rebranded in English from ViaMaker to CapCut and became available globally. It later expanded to include web and desktop versions for Mac and Windows. In 2022, CapCut reached 200 million active users. According to The Wall Street Journal, in March 2023, it was the second-most downloaded app in the U.S., behind that of Chinese discount retailer Temu. In January 2025, CapCut had over 1 billion downloads on the Google Play Store. On February 1, 2021, CapCut Pro for Windows was launched. On November 27, the Pro version for Mac was launched. In July 2025, CapCut Pro for HarmonyOS was available on HarmonyOS NEXT tablets. In July 2024, CapCut was reported by the South China Morning Post to be a generative AI (GenAI) application that led global AI app downloads, with approximately 38.42 million downloads and 323 million monthly active users. == Features == CapCut supports basic video editing functions, including editing, trimming, and adding or splitting clips. Editing projects is limited to single-layer editing, but the app supports overlay options that enable additional effects, including multi-layer editing. The app includes a library of pre-made templates and a tool that generates editable video captions. It also provides photo editing tools, including retouch and product photo features integrated within the editing interface. CapCut's video editor includes AI-based features such as video and script generation. Users can export or save completed projects directly to different social media platforms. CapCut includes a free version and a paid Pro version with cloud storage and advanced features. == Controversies == === Illegal data collection === In July 2023, many users of CapCut accused it of illegally profiting off their personal data. A class-action lawsuit filed in the U.S. District Court for the Northern District of Illinois on July 28, 2023, alleged that CapCut illegally harvests and profits from user data including biometric information and geolocation without consent. In September 2025, a federal court excluded most of the lawsuit, which alleged that TikTok’s parent company improperly scraped private data from CapCut's video editing software, as lacking grounds, with some of the class action continuing to move forward. == Bans and restrictions == === Ban in India === As a response to border clashes with China in May 2020, the Indian government banned around 56 Chinese applications including CapCut and TikTok, which is owned by CapCut's parent company ByteDance. Indian users were unable to use and download the application. As of February 2022, around 273 Chinese applications have been banned by the Indian government under the concern of national security and Indian user privacy. === Ban in the United States === On January 18, 2025, at 10 PM EST, CapCut was banned in the United States along with TikTok and all other ByteDance apps due to the implementation of the Protecting Americans from Foreign Adversary Controlled Applications Act. Hours after the suspension of services took effect, President Donald Trump indicated on Truth Social that he would issue an executive order on the day of his inauguration "to extend the period of time before the law's prohibitions take effect". On January 21, CapCut began restoring service. On February 13, Google and Apple restored CapCut on the App Store and Google Play Store.
AutoGPT
AutoGPT is an open-source autonomous software agent that uses OpenAI's large language models, such as GPT-4, to attempt to achieve a goal specified by a user in natural language. Unlike chatbots that require continuous user commands, AutoGPT works autonomously by breaking the main goal into smaller sub-tasks and using tools like web browsing and file management to complete them. Released in March 2023, the project quickly gained popularity on GitHub and social media, with users creating agents for tasks like software development, market research, and content creation. One notable experiment, ChaosGPT, was tasked with destroying humanity, which brought mainstream attention to the technology's potential. However, AutoGPT is known for significant limitations, including a tendency to get stuck in loops, hallucinate information, and incur high operational costs due to its reliance on paid APIs. == Background == AutoGPT was released on March 30, 2023, by Toran Bruce Richards, the founder of video game company Significant Gravitas Ltd. It was one of the first widely accessible applications to showcase the autonomous capabilities of GPT-4, which had been released weeks earlier. Richards's goal was to create a model that could respond to real-time feedback and pursue objectives with a long-term outlook without needing constant human intervention. The application operates by prompting a user to define an agent's name, role, and main objective, including up to five sub-goals to achieve it. AutoGPT then works independently to reach its objective. The project is publicly available on GitHub but requires users to install it in a development environment like Docker and have a paid OpenAI account to obtain the necessary API key. In October 2023, the project's parent company, Significant Gravitas Ltd., raised $12 million in venture funding to support further development. == Capabilities == The overarching capability of AutoGPT is the breaking down of a large task into various sub-tasks without the need for user input. These sub-tasks are then chained together and performed sequentially to yield a larger result as originally laid out by the user input. One of the distinguishing features of AutoGPT is its ability to connect to the internet. This allows for up-to-date information retrieval to help complete tasks. In addition, AutoGPT maintains short-term memory for the current task, which allows it to provide context to subsequent sub-tasks needed to achieve the larger goal. Another feature is its ability to store and organize files so users can better structure their data for future analysis and extension. AutoGPT is also multimodal, which means that it can take in both text and images as input. With these features, AutoGPT is claimed to be capable of automating workflows, analyzing data, and coming up with new suggestions. == Applications == === Software === AutoGPT can be used to develop software applications from scratch. AutoGPT can also debug code and generate test cases. Observers suggest that AutoGPT's ability to write, debug, test, and edit code may extend to AutoGPT's own source code, enabling self-improvement. === Business === AutoGPT can be used to do market research, analyze investments, research products and write product reviews, create a business plan or improve operations, and create content such as a blog or podcast. One user has used AutoGPT to conduct product research and write a summary on the best headphones. Another user has used AutoGPT to summarize recent news events and prepare an outline for a podcast. === Other === AutoGPT was used to create ChefGPT, an AI agent able to independently explore the internet to generate and save unique recipes. AutoGPT was also used to create ChaosGPT, an AI agent tasked to “destroy humanity, establish global dominance, cause chaos and destruction, control humanity through manipulation, and attain immortality”. ChaosGPT reportedly researched nuclear weapons and tweeted disparagingly about humankind. == Limitations == AutoGPT is susceptible to frequent mistakes, primarily because it relies on its own feedback, which can compound errors. In contrast, non-autonomous models can be corrected by users overseeing their outputs. Furthermore, AutoGPT has a tendency to hallucinate or to present false or misleading information as fact when responding. AutoGPT can be constrained by the cost associated with running it as its recursive nature requires it to continually call the OpenAI API on which it is built. Every step required in one of AutoGPT's tasks requires a corresponding call to GPT-4 at a cost of at least about $0.03 for every 1000 tokens used for inputs and $0.06 for every 1000 tokens for output when choosing the cheapest option. For reference, 1000 tokens roughly result in 750 words. Another limitation is AutoGPT's tendency to get stuck in infinite loops. Developers believe that this is a result of AutoGPT's inability to remember, as it is unaware of what it has already done and repeatedly attempts the same subtask without end. Andrej Karpathy, co-founder of OpenAI which creates GPT-4, further explains that it is AutoGPT's “finite context window” that can limit its performance and cause it to “go off the rails”. Like other autonomous agents, AutoGPT is prone to distraction and unable to focus on its objective due to its lack of long-term memory, leading to unpredictable and unintended behavior. == Reception == AutoGPT became the top trending repository on GitHub after its release and has since repeatedly trended on Twitter. In April 2023, Avram Piltch wrote for Tom's Hardware that AutoGPT 'might be too autonomous to be useful,' as it did not ask questions to clarify requirements or allow corrective interventions by users. Piltch nonetheless noted that such tools have "a ton of potential" and should improve with better language models and further development. Malcolm McMillan from Tom's Guide mentioned that AutoGPT may not be better than ChatGPT for tasks involving conversation, as ChatGPT is well-suited for situations in which advice, rather than task completion, is sought. Will Knight from Wired wrote that AutoGPT is not a foolproof task-completion tool. When given a test task of finding a public figure's email address, he noted that it was not able to accurately find the email address. Clara Shih, Salesforce Service Cloud CEO commented that "AutoGPT illustrates the power and unknown risks of generative AI," and that due to usage risks, enterprises should include a human in the loop when using such technologies. Performance is reportedly enhanced when using AutoGPT with GPT-4 compared to GPT-3.5. For example, one reviewer who tested it on a task of finding the best laptops on the market with pros and cons found that AutoGPT with GPT-4 created a more comprehensive report than one by GPT 3.5.