AI Research
Trump loves AI, and the MAGA world is getting worried

Rep. Marjorie Taylor Greene (R-Ga.) fired off a tirade on X, complaining that AI could create mass poverty by replacing human jobs, and giant AI data centers could have potentially devastating effects on the environment and water supply.
In the days that followed, GOP strategist Steven Bannon chimed in, comparing the pursuit of AI superintelligence to “summoning the demon.” And since then, think-tankers and populist conservative outlets have continued to stoke worries about federal policies that turbocharge AI development.
On stage at the National Conservatism conference in Washington in early September, Sen. Josh Hawley (R-Mo.) criticized the AI revolution as a leap towards transhumanism — a human-machine future that he said is currently against “the working man” and the teachings of the Bible, as well as installing “a rich and powerful elite.”
“Americanism and the transhumanist revolution cannot coexist,” Hawley said — a declaration met with spontaneous applause from the audience.
Asked about conservative concerns regarding the Trump administration’s AI plans, White House spokesperson Liz Huston did not acknowledge the criticism, responding: “President Trump is committed to maintaining US dominance in AI over China. By fully harnessing the power of AI, we will unleash this productivity for the full benefit of workers while driving down costs for services and goods to make America more affordable.”
For their part, the populist conservatives won a round in Washington over the summer, killing off a proposed moratorium in Congress that would discourage states from making AI regulations for a decade. Many GOP senators and attorneys general objected that it would prevent their own states from enforcing their own laws to rein in Big Tech.
“The base’s concerns about Big Tech are colliding with Silicon Valley’s influence in this administration,” said Mark Beall, a tech-skeptical conservative who runs government affairs for the AI Policy Network, a bipartisan nonprofit that advocates for some guardrails on powerful AI.
Conservative populists have also targeted other aspects of Trump’s AI policy.
One is copyright law — a normally obscure issue that has become a political flashpoint in the age of AI, since tech companies train their models on vast quantities of copyrighted material.
Trump introduced his AI plan with a long, seemingly improvised riff about copyright law, agreeing with AI companies that it needs to be loosened up. Bannon is directly opposed to that idea, and has run numerous War Room podcasts objecting to AI companies’ free use of copyright material, calling it outright “theft.”
In an interview two weeks after Trump’s announcement, Sen. Hawley also used the word “theft,” telling POLITICO that congressional inaction on the issue could lead to “the largest intellectual property theft in American history.”
The senator, a longtime critic of Big Tech, has a bill in Congress to bar AI companies from training on copyrighted material without authors’ consent. He says he agrees with Trump on one point — that it’s infeasible to micromanage individual authors’ work — but wants to create a licensing regime rather than leaving it a free-for-all.
It’s not clear whether Hawley’s bill will move forward, but several other AI bills could be considered this fall, including Sen. Ted Cruz (R-Tex.)’s proposed “sandbox” legislation to grant AI companies regulatory waivers as they experiment with the technology, and Sen. Chuck Grassley (R-Iowa)’s bill to protect AI-related whistleblowers from employment discrimination.
Bannon and Greene could not be reached for questions on the issue, including whether they’d try to mobilize voters against pro-AI legislation.
Wynton Hall, social media director at Breitbart, the right-populist site whose tech coverage has gone heavy on critiques of AI, said in an interview that he sees a brewing concern in the MAGA base over AI’s impact on humanity.
“There is within the conservative movement certainly a concern about child safety, mental health, all those things,” he said. He also sees AI-related job loss as a growing political issue on the right.
“The transhumanism stuff is also a real concern for conservatives,” he added.
Though that concept might seem obscure, it has already come up in Capitol Hill debates. In a June hearing of the House Oversight Committee, Republicans Scott Perry (R-Pa.), Anna Luna (R-Fla.) and Eli Crane (R-Ariz.) all pushed back strongly against the notion of AI supplanting humans.
“AI lacks a few things — one being a soul, and also empathy. And we are not gods or God,” said Luna. She raised concerns about whether AI-driven technologies would ultimately prioritize human safety, or work against it.
“The Republican base is just not where the tech accelerationists are,” said Brendan Steinhauser, a GOP strategist who now leads the Alliance for Secure AI, a bipartisan nonprofit trying to push a middle-ground approach to AI guardrails.
An early organizer in the Tea Party movement circa 2008, Steinhauser thinks there will be a political backlash soon from parents and family members over the technology’s impact on the psyche, as well as morally concerning trends like creating lifelike revivals of dead people, or increasingly human-like AI companions.
His concerns are echoed by Beall, who wrote a widely circulated July essay published just before the Trump AI Action Plan titled, “A Conservative Approach to AGI.” (“AGI” refers to artificial general intelligence, or super-powerful AIs.) He argues that the industry’s race to develop superintelligent systems is a reckless attempt to build “self-creating gods” that flouts any coherent theology of man’s limitations.
So far, however, Trump’s AI plans have paid little heed to those concerns, favoring acceleration over caution. A former GOP strategist — granted anonymity to discuss the influence of their tech industry clients — noted that strongly held populist arguments often collapse against the financial and political weight of Silicon Valley.
“Traditional conservative theory is a bit of an anachronism nowadays,” the political strategist said, adding that it doesn’t always “survive a run-in with the amount of money and the level of influence buying that is now fully socialized as normal.”
It’s not clear whether AI will gain the political traction of other Big Tech issues, like the “free speech” campaign to stop tech companies from de-platforming conservative voices on social media.
Hall said the political consequences would likely be felt later — once it becomes clear how widespread and severe AI-related job loss would be.
“That’s the big trillion-dollar question,” he said.
AI Research
How Skywork AI’s Multi-Agent System Simplifies Complex AI Tasks

What if there was a tool that didn’t just assist you but completely redefined how you approach complex tasks? Imagine a system that could seamlessly browse the web for critical data, write detailed reports, and even build custom tools on the fly, all while collaborating with specialized agents designed to tackle specific challenges. Enter the Deep Research Agent, a new innovation by Skywork AI. This isn’t just another AI framework; it’s a multi-agent powerhouse that combines innovative models, dynamic tool creation, and unparalleled adaptability to handle tasks with precision and efficiency. Whether you’re a researcher, developer, or strategist, this system promises to transform how you work.
Prompt Engineering explain the intricate architecture behind the Deep Research Agent, including its Agent Orchestra framework, which enables seamless collaboration between specialized agents. You’ll discover how this open source tool doesn’t just solve problems but evolves to meet unique challenges by creating and managing tools in real-time. From automating web browsing to generating actionable insights, the possibilities are vast, and the implications for industries ranging from tech to media are profound. By the end, you might just find yourself rethinking what’s possible in task automation.
Deep Research Agent Overview
TL;DR Key Takeaways :
- The Deep Research Agent by Skywork AI is an open source, multi-agent framework designed for precision and adaptability, capable of handling tasks like web browsing, document generation, data analysis, and tool synthesis.
- The “Agent Orchestra” framework enables collaboration among specialized agents, dynamically creating and managing tools to address unique and complex challenges across industries.
- Specialized agents, such as the Deep Analyzer, Deep Researcher, Browser Use Agent, and MCP Manager, work together to deliver efficient and precise results for diverse tasks.
- A key feature is dynamic tool creation, allowing the system to synthesize, validate, and register new tools when existing ones are insufficient, making sure continuous adaptability and tailored solutions.
- The framework integrates multiple AI models, supports local and remote tools, and is open source on GitHub, making it accessible and customizable for various applications, from document creation to market research and API integration.
The Agent Orchestra Framework: A Collaborative Core
At the heart of the Deep Research Agent lies the “Agent Orchestra,” a hierarchical framework that orchestrates the collaboration of specialized agents. Each agent is carefully designed to excel in specific tasks, working in unison to tackle complex challenges. The framework’s adaptability stems from its ability to dynamically create and manage tools, making sure it can address unique requirements, even when existing tools are insufficient. This dynamic approach allows the system to evolve continuously, offering tailored solutions to meet the demands of various industries.
Specialized Agents: Precision in Action
The Deep Research Agent employs a suite of specialized agents, each functioning as an expert in its domain. These agents work collaboratively to deliver precise and efficient results:
- Deep Analyzer Agent: Performs in-depth analysis to extract actionable insights from diverse data types, allowing informed decision-making.
- Deep Researcher Agent: Synthesizes information from extensive research, producing detailed reports, summaries, and comprehensive insights.
- Browser Use Agent: Automates web browsing to streamline data collection, making sure efficient and accurate information extraction.
- MCP Manager Agent: Oversees tool discovery, registration, and execution using the MCP protocol, making sure seamless tool integration and management.
Skywork AI’s Multi-Agent System : Browses, Writes and Builds Tools
Here is a selection of other guides from our extensive library of content you may find of interest on multi-agent framework.
Dynamic Tool Creation: Tailored Solutions
A standout feature of the Deep Research Agent is its ability to dynamically create tools. When existing tools fail to meet specific requirements, the system synthesizes new ones, validates their functionality, and registers them for future use. This capability ensures the framework remains adaptable and responsive to evolving needs, providing customized solutions for even the most intricate challenges. By continuously expanding its toolset, the system enables users to tackle tasks with unparalleled efficiency and precision.
Applications Across Industries
The versatility of the Deep Research Agent makes it an invaluable tool across a wide range of industries and tasks. Its applications include:
- Document creation, including the generation of Word documents, PDFs, and presentations tailored to specific needs.
- Data analysis, such as trend visualization, market insights, and real-time updates to Excel spreadsheets.
- Web development and comprehensive market research to support strategic decision-making.
- API integration for custom workflows, allowing seamless automation and enhanced productivity.
Technological Features: Innovation at Its Core
The Deep Research Agent incorporates advanced technologies to deliver exceptional performance and flexibility. Key features include:
- Integration of multiple AI models: Combines the strengths of OpenAI, Google, and open-weight models to achieve superior results.
- Support for local and remote tools: Offers maximum adaptability by seamlessly integrating tools across different environments.
- Open source availability: Accessible on GitHub, allowing users to customize and experiment with the framework to suit their specific needs.
Skywork AI’s Broader Vision
Skywork AI’s innovations extend beyond the Deep Research Agent, showcasing a commitment to advancing AI capabilities across various domains. The company’s other new projects include:
- 3D world generation from single images, transforming virtual environments and simulations.
- Open source multimodal reasoning models designed for complex problem-solving and decision-making.
- Infinite-length film generative models, pushing the boundaries of creative AI applications in media and entertainment.
- Image generation, understanding, and editing tools for diverse creative and analytical purposes.
Performance and Accessibility: Designed for Users
The Deep Research Agent has demonstrated exceptional performance, achieving high scores on GAIA and humanity benchmark tests. Its ability to deliver state-of-the-art results across various applications underscores its reliability and efficiency. For users, the framework offers API access for tasks such as document creation and data analysis. To encourage adoption, free credits are provided for initial testing, with tiered packages available for extended use. This accessibility ensures that organizations and individuals can use the system’s capabilities without significant barriers.
Setting a New Standard in Task Automation
The Deep Research Agent represents a fantastic advancement in multi-agent frameworks, combining precision, adaptability, and scalability. By integrating advanced AI models, dynamic tool creation, and open source accessibility, it establishes a new benchmark for task-solving systems. Whether automating workflows, conducting in-depth research, or exploring creative applications, this framework offers a robust and versatile solution tailored to meet the demands of modern industries.
Media Credit: Prompt Engineering
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AI Research
Artificial intelligence is becoming essential to job security – CBS News
AI Research
The good, the bad and the worrisome: UW professor explains how AI is shaping our lives

As an educator, Lisa Mitchell uses artificial intelligence (AI) to “help think of ideas,” which she then edits into something that she wants and can use for her classes.
“[AI] can save us time from doing some tasks as long as we’re knowledgeable enough to edit those ideas that it provides,” she told CBC News on a sunny day in downtown Kitchener last week.
AI can be a very useful application, said Joel Blit, who is an associate professor of economics at the University of Waterloo.
Blit is also the co-founder and co-director of the Canadian AI Adoption Initiative. He said that after ChatGPT was launched around three years ago, AI became a “fundamentally democratic technology.”
“Now people can use AI, interact with AI in natural language,” he said. “Every Canadian can use the technology to do things faster, better, more efficiently, or even do things that they weren’t able to do before.”
But while AI is useful in her line of work, Mitchell says she’s worried about the risks surrounding its growing use — a worry that Blit said he recognizes.
To Blit, these worries about AI are valid. But as an expert who works with executives and leaders in government to “seize the benefits of AI,” he says we need to find the balance between regulating AI and using it for its strengths.
AI is transforming the way people operate
Julia Guenther said she uses AI “quite a bit,” especially in condensing information in a way that would make it easily understandable for a wide range of users.
Guenther also spoke to CBC News during her lunch break in downtown Kitchener She said she uses AI to do some translating tasks, but that she has someone else look at it afterwards.
“It still has to get reviewed by an individual who is familiar with the language it’s translated to,” she said. “But it does make it easier and simpler for them, at least if they have a starting point from what it is that I provided.”
These are just some of the applications of AI that people know about. Blit said many people don’t realize that digital assistants like Siri and Alexa also use AI. Even Google Maps use AI as well, he explained.
Apart from these common applications, Blit says AI is also being utilized for things like customer service, HR tasks, marketing, and even healthcare.
“My wife is a family doctor and she’s been using the AI scribe… it saves her probably about 20 per cent of her time,” he said.
“It’s a great example because it means that you can be fully engaged with the patient instead of writing as the patient is explaining.”

But while AI can help make previously tedious tasks more convenient, relying too much on AI will result in some undesired effects.
On an individual level, Blit explains that relying on AI could affect people’s ability to organize their thoughts.
“I think, maybe, we do start to lose a little bit of our ability to organize our thoughts if AI is doing it for us,” he said.
But at the same time, Blit says using AI will not cause people to just suddenly lose the ability to think.
Blit compares the situation with AI to using calculators, saying that people did not lose the capacity to do arithmetic just because the calculator was invented.
“We now focus on other aspects other than arithmetic because we have the calculator,” he said. “It’s just going to be the same thing with the AI… we’re going to do less of the things that AI does well, and more of the things that it doesn’t do as well.”
A ‘super intelligence’ in the next 20 years
In 2024, British-Canadian computer scientist Geoffrey Hinton told CBC News that research suggests that there is about a 50 per cent chance a “super intelligence” will be developed in the next 20 years.
“We will make things smarter than ourselves,” Hinton said. “It’s mainly a question of whether governments can regulate the big companies so that they develop AI safely.”

Hinton is often lauded as one of the “godfathers of AI.” He says the world’s governments need to “force the big companies to do more research on how to keep these things safe when they develop them.”
Blit agrees that AI needs to be regulated because there are no specific regulations for it. He says currently, there are only “general regulations that would apply to many uses of AI.”
But at the same time, Blit says there is a need to ensure that AI is not being over-regulated.
“If we do, we are going to stifle the technology, we’re going to stifle the innovation that frankly, as a country, we need,” he said.
AI will affect jobs; Blit, Québec study
Another common question surrounding the growing adoption of AI in the workplace is how it will affect people’s jobs.
Blit recognizes that AI will bring about change, and says the transition period is “going to be difficult,”
“You can’t put your head in the sand and pretend that this is not happening because it is going to happen,” he said.
In January, the Institut du Québec, in collaboration with the Future Skills Centre, conducted a study on AI’s impacts on jobs in Québec. The study found that in the next 10 years, an estimated 800,000 Québec jobs could be affected by AI.
Some of the jobs that could be affected include, but are not limited to, cashiers, waiters, auditors, machine operators, among others.
In King City, Ont., for example, a lettuce farmer is tackling Canada’s reliance on U.S. greens by utilizing AI to run his lettuce farm.
The farm’s owner, Jay Willmot, says that automating his greenhouse allowed him to “maximize the amount of lettuce he can grow, while cutting labour costs.” Labour costs are typically a greenhouse grower’s biggest operating expense.

But Blit says what’s likely to happen is not straightforward.
“I think that the reality is that you’re not going to lose your job to AI,” he said. “You’re more likely to lose your job to someone that is using AI to do your job better.”
Guenther agrees, saying that AI will help improve people’s speed, efficiency, and ability to do tasks.
“But I don’t think that it’s going to take away from the workforce,” she said.
With worries surrounding AI growing, Blit said he found that approaching its use from an “experimental point of view” can really help alleviate some of those worries.
“When [people] start experimenting with it, they realize that actually [AI] is not too bad,” he said. “It just blows you away until you sort of get used to it.”
“The first thing that I think everybody needs to know is… you can use [AI] too.”
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