The Rundown AI: How to use Grok for free automated research


🔎 How to use Grok for free automated research
The Rundown: In this guide, you will learn how to use Grok’s Tasks feature. If you have a free X.com account, you get 2 automated tasks each day — use them to build automated daily research briefings pulled from live X data.
Step-by-step:
Go to Grok and sign in with your X account. Click on your profile picture in the bottom left, then click Tasks in the pop-up

Click New Task, give it a name, set your schedule (daily, weekly, or specific days), and prompt: “Search X for the top trends in [your niche] from the last 24 hours. Summarize the top 3 and flag anything gaining traction”Once you save the task, Grok will run the search on schedule and send you the results via email and as a push notification in the mobile appTo view run results on desktop, navigate back to grok.com/tasks and click on the task.
Pro tip: In addition to your two daily tasks, you can also stretch your free Grok account further by scheduling up to 10 research tasks per week or month.
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Futurism: “Ketamine”. Essential reading.

Judge Rules That Elon Musk’s Ketamine Use Is Off Limits

Hands off!

By Frank Landymore

Published Mar 17, 2026 7:00 AM EDT

A close-up portrait of Elon Musk wearing a black cap and black jacket, looking to the right. The background features a green grid pattern with a large red circle behind his head. The image has a slightly desaturated, vintage tone.
Illustration by Tag Hartman-Simkins / Futurism. Source: Kevin Dietsch / Getty Images

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“Leave Britney alone!” — remember that one? — seems to be the thrust of a judge’s recent ruling in an ongoing legal feud between Elon Musk and OpenAI.

At a Friday hearing in California, US District Judge Yvonne Gonzalez Rogers said that Musk’s use of ketamine will be off limits to OpenAI’s legal team and its CEO Sam Altman as the case is set to go to trial next month, Bloomberg reports, which will likely save Musk from heaps of further embarrassment.

Musk allegedly has, or had, a heavy ketamine habit. Many had long speculated, including those close to the man himself, that Musk recreationally used the tranquilizer, which is known for its hallucinogenic effects, claims fueled by his own admitting to using the drug under a prescription to treat depression.

For years, major media outlets intensified the scrutiny. In 2024, The Wall Street Journal reported that Musk used LSD, cocaine, ecstasy, and mushrooms, often at drug-fueled parties. Sources close to him said that his use of ketamine was still ongoing, raising the possibility that Musk could be jeopardizing his companies’ federal contracts with his illegal habit.

But in 2025, the story hit another level. That May, a report from the New York Times claimed Musk was using recreational drugs far more than what was previously known. He reportedly brought a daily pillbox that held about 20 capsules with him wherever he went, stuffed with drugs like Adderall. He was taking ketamine almost every day, according to the reporting, sometimes combining it with other substances of choice — a drug habit so severe that he reportedly confided in others that it was causing bladder issues.

With Musk being a key figure behind Donald Trump’s re-election campaign, and at the time of reporting actively involved in gutting the federal government through his pet project DOGE, it became not just Wall Street-flavored tabloid gossip, but a genuine political issue. Grilled by the press about the allegations after his public fallout with Musk, Trump could not rule out the possibility that his billionaire “First Buddy” took drugs while physically in the White House. “I really don’t know,” Trump said. “I hope not.”

As experts noted, a ketamine habit could explain years of increasingly bizarre and erratic behavior from Musk, especially at public gatherings. To wit: acting blasted out of his mind — and conspicuously wearing shades — when he waved a literal chainsaw around on stage at a Conservative Political Action Conference last summer to symbolize his slashing of federal spending, or losing control of his facial muscles in spaced-out fashion before giving Nazi salutes.

In any case, all of this is apparently moot in the upcoming trial, which concerns Musk’s allegation that OpenAI abandoned its roots as a non-profit concerned with pursuing the public good. Musk cofounded OpenAI with Altman but left in 2018, reportedly due to beefing with Altman’s leadership. Musk filed the suit in 2024, attempting unsuccessfully to block the company’s restructuring into a for-profit public benefit corporation, which it completed last year. It’s now reportedly seeking to go public, in what is anticipated to be a historic trillion dollar IPO.

Judge Gonzalez Rogers said that OpenAI could not try to discredit Musk on the witness stand by asking him about his alleged ketamine use during negotiations with the company because they would be irrelevant unless OpenAI could provide more evidence on the tranquilizer’s mind-altering effects, per Bloomberg.

The judge, however, said she would allow limited questioning about Musk attending Burning Man, a trippy festival that takes place in the middle of the Nevada desert known for its drug-fueled debauchery. OpenAI lawyers claimed a “lot of significant communications” between Musk and OpenAI happened while he was at Burning Man.

Musk is now seeking as much as $134 billion in damages from OpenAI and Microsoft, which heavily invested in the ChatGPT maker after his departure.

More on Elon Musk: Elon Musk Just Made a Small Change That Speaks Volumes About His Desperation

Frank Landymore

Contributing Writer

I’m a tech and science correspondent for Futurism, where I’m particularly interested in astrophysics, the business and ethics of artificial intelligence and automation, and the environment.

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George Galloway MOATS. Interview with Chris Hedges. The madness of The Donald

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DW: Epstein and more

https://p.dw.com/p/5ALa7

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Tom Wright on X: Anthropic AI models evolving in odd and unanticipated ways ….

Tom Wright

@thomaswright08

This is very concerning. Anthropic’s point, as I understand it, is that all AI models are evolving in odd and unanticipated ways which means we need to be very careful before deploying them in fully autonomous systems without human oversight. They have been transparent and rigorous in ways that some other companies have not been. Here

@USWREMichael

is implying that only Anthropic’s models are uniquely problematic and others are better and work as intended. If he actually believes this, there’s a significant risk of a systemic failure that will hurt US interests.

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GZEROWORLD: Endgame in Iran? Chaos in the Middle East … Ian Bremmer

Endgame in Iran?

GZERO Media

March 16, 2026

The war in Iran has escalated quickly, with the US, Israel, and Tehran pursuing diverging strategies. As the conflict intensifies, the chance of a short, clean exit for President Trump is slowly slipping away, with munitions stretched thin, oil prices spiking, and no clear path forward.

Thomas Wright, former Senior Director at the US National Security Council, calls it “by its very nature
 a war of choice. There was no reason necessarily to do it.” He notes that while the US hopes for a pragmatic partner in Tehran, Israel seeks full regime change. Wright warns that attempts to fragment Iran could backfire, creating a “much bigger headache than managing a regime that was already at its weakest point since 1979.” While strikes have weakened Iran’s nuclear program, further action risks regional chaos.

Looking ahead, Wright outlines potential outcomes, from the best-case scenario of a more legitimate, if not democratic, regime, to the worst-case scenario of a fragmented Iran. For now, Trump faces a far more complex and dangerous environment than he may have anticipated.

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Nature + a little assistance from AI: ‘Einstein’ bot sharpens debate over AI in the classroom. Could it be the death of education as we know it.

  • CAREER NEWS
  • 12 March 2026

‘Einstein‘ bot sharpens debate over AI in the classroom

Faculty members are spending ever more time outmanoeuvring students who want to cut corners with artificial intelligence.

By 

Black and white archive image of Albert Einstein in his younger years.
An AI tool named after Albert Einstein (pictured) was taken down shortly after it was released.Credit: GK History Images/Alamy

On 23 February, academics across the world took to social media to decry the death of education as we know it. The day before, a technology start-up company called Companion had released an artificial-intelligence platform that pledged to free students from tedious coursework.

Such a statement might not seem controversial at a time when AI tools exist for nearly everything, if not for the fact that the program, called Einstein, promised on its website to do so much more. The company said that students could grant the tool access to their account on a virtual learning environment, such as Canvas. Once they did that, Einstein could watch lectures, read course material, participate in discussions, complete quizzes, and write and submit homework — all with minimal oversight by the student themselves.

Companion chief executive Advait Paliwal told the technology news outlet CNET that Einstein “makes ChatGPT look like a toy”, whereas educators called it “a cheating app”, “evil” and “the ultimate brain smoothing machine”. Language on the tool’s website shifted after the backlash to downplay the AI’s capabilities, and by 26 February, the bot was no longer accessible after a ‘cease-and-desist’ demand. Paliwal told Times Higher Education that he would now “concentrate on promoting how the wider Companion AI can be used by students”. (Attempts by Nature to reach Paliwal received no reply.)

Game over

Einstein’s moment in the Sun might have been short, but it is part of a wider reckoning over how students should be educated today. AI tools are being marketed as time savers for teachers overburdened by administrative tasks, and yet some faculty members are instead spending more time on battling bad-faith uses involving students, resulting in a push to return to ‘de-digitized’ curricula that place less emphasis on computers.

“My first thought when I saw Einstein was ‘game over’,” says Lilian Edwards, a specialist in Internet law and technology policy at Newcastle University, UK, because circumventing it would require instructors “to rearrange [their] assessment strategy entirely”, which would involve substantial effort. “AI can certainly be useful,” she adds, but the majority of people she knows “think it’s driving a stake through the heart of conventional educational assessment”.

AI has lots of legitimate uses in academia — including writing code, translating texts and correcting grammar — and David Jurgens, a computer scientist at the University of Michigan in Ann Arbor, says it’s nearly impossible to avoid in his field. As such, he often faces many of the same ethical quandaries as his students. Jurgens came across another AI, called Professor Feynman, which is essentially Einstein for academics: it promises to free them from the ‘busywork’ of reading and grading essays, responding to discussions and even the need to offer online office hours, by creating a ‘digital twin’ that mimics their voice, mannerisms and teaching style.

“You can imagine a nightmare situation where classes become AIs talking to AIs, with no people actually interacting,” he says.

Rather than adapting his assessments to AI platforms, Jurgens has engaged his students in thoughtful discussions in the classroom.

“Teachers are always going to have to spend time developing and updating their curriculums, and so I’ve tried to make it a more collaborative process,” he says. “It feels like a better use of my time, and as a result, I do see students being more aware that they’re only hurting themselves in the long term if they’re replacing themselves with these tools.”

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The article concludes by highlighting potential solutions and ethical considerations around AI in education. After discussing the “Professor Feynman” AI tool for academics and the nightmare scenario of AIs interacting without human involvement, it returns to David Jurgens’ approach: instead of overhauling assessments to counter AI, he focuses on in-class discussions and collaborates with students on curriculum updates. This fosters awareness among students that over-relying on AI ultimately harms their own learning and development in the long term.The piece ends there, transitioning into related content like a collection on ChatGPT’s impact on science careers, along with links to other articles such as “‘Without these tools, I’d be lost’: how generative AI aids in accessibility” and “ChatGPT for students: learners find creative new uses for chatbots.” The DOI is https://doi.org/10.1038/d41586-026-00764-w.

nature.com

1 web page

Explain Professor Einstein bot

AI ethics in higher education

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Not Ireland anymore … Eoin Lenihan gives voice to what many people feel

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Professor Mearsheimer talks to Chris Hedges: Iran’s GRAND STRATEGY. WHAT WILL THE US DO?

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The Deep View: Secret Sauce

SECRET SAUCE
Repository intelligence: Giving agents a memory
Jason Hiner: This idea of repository intelligence is really where GitHub sees itself as a layer above even all of the different coding assistants, a way for you to provide added value, knowing that companies and coders are using multiple coding assistants. What does repository intelligence mean and what can it offer?
Mario Rodriguez: Today, all of the world’s code lives on GitHub. We see all of the commits that are happening. We see all of the pull requests. We see the issues. So there are all of these artifacts that come into play as you develop in a team context, and all of those go through GitHub.
Repo intelligence is the ability to say, look, it’s not just the code. It’s the entirety of the repo and all of the artifacts that go into creating a feature, and then being able to index that, provide midterm and long-term memory on it, and really start thinking through it as a graph of work for software development.
Imagine if I’m joining a new company and a new code base. I could go in and not only look at the code, but say: What were all the decisions that came into being? How did they develop it? What were the prompts they used? Did the quality get better or not, and when it didn’t, why not? What was super successful that ended up impacting the business? We did a migration to this library, then migrated away. Why? That’s what repo intelligence is all about. It’s that institutional memory plus expertise at any point in time. And then imagine every agent being able to query that and utilize it to get something done.
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