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Received — 29 July 2026 ⏭

AI Companies Are Recruiting Electricians and Carpenters By the Thousands

✇Slashdot
By: BeauHD
29 July 2026 at 22:30
An anonymous reader quotes a New York Times report on how AI companies are pouring money into training and recruiting electricians, carpenters, and other skilled tradespeople to build data centers: There is no parallel in American history for the boom underway in the construction of data centers, fueled by companies with functionally unlimited cash that are racing to supply skyrocketing demand for their A.I. models. The explosion has offset flagging activity in other sectors, like office construction, which never recovered after the pandemic. Housing has been depressed by high interest rates, and offshore wind felled by political opposition. Still, competition for labor -- never mind land and materials -- is starting to weigh on other parts of the industry. "There's no question the resources are very limited, so decisions to build one thing kind of drag from another," said Mario Iacobacci, who runs the construction and infrastructure advisory practice at Oxford Economics. Developers are paying a premium for workers, especially in the rural areas where they are building data centers. According to an analysis by Indeed, the job listings website, hourly installation and maintenance jobs at data centers pay 42 percent more than similar jobs in other fields. Behind that inflated pay is a bidding war. In markets with a lot of data center construction, like Dallas and Northern Virginia, workers can jump ship for bonuses or higher per diem rates. The competition has driven contractors to staffing services like Aerotek. "It is creating a labor tension that is really delicate," said Marty Schager, Aerotek's director of data center market development. "You've got a passive job-seeker community out there right now that I think is looking to potentially capture opportunity with this once-in-a-generation data center gold rush." [...] The question looms over the apprentices who will become journeymen as the build-out reaches fever pitch. Fully trained electricians could shift to nuclear plants, apartment buildings or pharmaceutical factories. But it's hard to imagine anything on the scale of what's underway. "The best-case scenario would be you train all these skilled workers up and right when the data centers start to become less popular is we'd have a housing boom," said Jeff Strohl, director of Georgetown University's Center on Education and the Workforce. "That's probably not likely." "If we have an influx of workers at this point with the data centers being built, what happens when they're done? Where do those workers go?" he said. "How many people does it take to run a data center after taking up all this property and all this land that could have been used for something else?"

Read more of this story at Slashdot.

Built a Notion CRM for agencies that were tired of losing track of leads

✇CRM - Customer Relationship Managment
By: /u/eve9656
29 July 2026 at 21:43

If you're a small agency owner and managing multiple clients, companies and deals at the same time, you've probably experienced at least one of these:

• Forgetting to follow up

• Losing track of deal status

• Having contacts scattered across different places

• Not knowing the real value of your pipeline

So I built this Notion CRM to solve those problems.

Problem: Losing track of which deals are active vs closed

Solution: Change one status, everything (companies, contacts, reports) moves automatically between Active/Won/Lost views

Problem: Forgetting to follow up until it's too late

Solution: Health check formula flags deals as On Track, Closing Soon, Late, or Done based on expected date

Problem: Not knowing real pipeline value

Solution: Weighted value formula calculates expected revenue based on deal stage a "New Lead" worth $10k isn't the same as a "Proposal Sent" worth $10k

submitted by /u/eve9656
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Who Wins and Who Loses After US Bans Foreign Robots?

✇Slashdot
By: BeauHD
29 July 2026 at 19:00
The FCC's ban on Chinese-made robots extends well beyond humanoids to quadrupeds, research platforms, and many robot vacuums from allied countries. Supporters call it a major boost for domestic robotics, but critics warn that cutting researchers and startups off from affordable foreign hardware could slow U.S. innovation instead. Ars Technica's Jeremy Hsu examines who stands to gain and who stands to lose from the prohibition: Such an import ban would apply to some of the most affordable robots primarily produced by Chinese companies, including Unitree's humanoid robots that are used by robotics labs and researchers for tasks such as experimental robot surgeries. US consumers would also likely lose access to the newest robot vacuum cleaners that are mainly manufactured by Chinese companies such as Roborock. But the ban also broadly applies to foreign-made robots produced by countries nominally allied to the United States, including Japan, South Korea, and Germany. [...] The ban on foreign-made robots could theoretically encourage more US and foreign companies to set up manufacturing facilities in the United States. There are already multiple companies racing to scale up production of humanoid robots in US factories, including Agility Robotics, 1X Technologies, and Figure AI. Tesla has been attempting to shift production away from older electric vehicle models and toward its Optimus humanoid robot. Boston Dynamics has already been making its Atlas humanoid robot, along with its four-legged Spot robot and wheeled Stretch robot, at its main facility in Waltham, Massachusetts. The US robotics company is also planning to massively scale up manufacturing of the Atlas robot under South Korea's Hyundai Motor Company, which gained full ownership of Boston Dynamics in July 2026. "This is one of the strongest technology-security actions in modern US history," wrote Evan Beard, CEO of Standard Bots, in a LinkedIn post. "The message is unambiguous: robotics is a technology America must lead and own -- and foreign-subsidized robots will not be allowed to unfairly dominate US robotics as they did solar." Similar praise came from Rush Doshi, director of the Initiative on China Strategy at the Council on Foreign Relations, who, in a social media post, described the FCC decision as "one of the most significant actions taken so far in support of the US robotics ecosystem." However, several robotics researchers and analysts interviewed by The Robot Report expressed skepticism about any potential boost to US competitiveness in robotics. Some even warned that the ban could prove counterproductive for US robotics efforts to develop humanoid robots. "In the near term, the measure could slow US physical AI innovation by cutting startups and researchers off from future low-cost Chinese platforms before comparable Western alternatives exist," said Georg Stieler, a global robotics advisor and managing director for Asia at Stieler Technology & Market Advisory, in an interview with The Robot Report. US domestic production of robots lags behind China in terms of mass manufacturing at lower cost, said Rueben Scriven, a senior analyst at Interact Analysis. "This announcement is more likely to inhibit the US humanoid robotics industry, as the presence of low-cost Chinese humanoid robots has been helping educate the US market through promotional and entertainment use cases -- an effect this policy risks undermining," Scriven told The Robot Report. The report notes that previous FCC bans have done little to help create competitive U.S. alternatives, with restrictions on Chinese drones instead prompting companies to sell barely disguised versions of DJI technology.

Read more of this story at Slashdot.

If you could rebuild your CRM from scratch, what would you change?

✇CRM - Customer Relationship Managment
By: /u/Axfrgo-the-Scientist
29 July 2026 at 18:29

I’ve spent the last year building a CRM/revenue platform, one thing I’ve realized is that everyone seems to hate something different about the software they already use but is it enough to switch?

Some people complain about data entry.
Others hate moving deals through pipelines.
Some spend hours creating quotes.
Others struggle with the handoff between sales and operations.

Before any useful tools can be built, we need to learn from people who use CRMs every day rather than assume we know the answers.

I personally come from a corporate energy and infrastructure role and the crm was the glue we used to hold our teams together but still each one had lacking capabilities which fostered the current platform I’ve built fortifiers.

So I’m not looking to promote anything but genuinely curious:

What’s the biggest frustration with your current CRM?
What’s one feature you wish existed but doesn’t?
If you could delete one part of your workflow forever, what would it be?
I’m not here to pitch anything. I’m genuinely trying to understand where existing CRMs still fall short. If anyone is interested in seeing what I’m building afterward, I’m happy to share it privately, but I’d value the discussion regardless.

submitted by /u/Axfrgo-the-Scientist
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Valve Sponsors Work Bringing Open-Source RADV Driver To Windows

✇Slashdot
By: BeauHD
29 July 2026 at 18:00
Valve is funding Collabora's experimental effort to port the open-source RADV Vulkan driver from Linux to Windows. The team has already demonstrated Counter-Strike 2 running with RADV, but a stable interface or compatibility shim will be needed to handle undocumented driver changes. Phoronix reports: Louis-Francis Ratte-Boulianne put out a blog post highlighting their initial work on porting RADV to Windows. Besides working on Windows WDDM2 integration for Windows, a big challenge with porting RADV to Windows is on relying on the AMD Radeon Software Windows kernel driver. It's out-of-scope of this current work for trying to port the AMDGPU Linux kernel graphics driver to Windows, so they are working on bringing RADV to Windows while relying on AMD's official Windows kernel driver. That in turn has led to reverse engineering and other steps for figuring out the proprietary kernel driver's data structures and other elements so RADV can be adapted to use it.

Read more of this story at Slashdot.

Google Shuts Down Its Nobel-Prize Winning AlphaFold Project

✇Slashdot
By: BeauHD
29 July 2026 at 17:00
Google has dismantled the original AlphaFold team, according to Financial Times (paywalled), reassigning many researchers to Gemini and Isomorphic Labs. Several other key members, including Nobel laureate John Jumper, left for Anthropic. Engadget reports: AlphaFold is an AI program that can accurately predict three-dimensional structures of proteins from their amino acid sequences in minutes instead of years. It's now being used to accelerate drug discovery, develop vaccines and understand the structural changes in proteins associated with neurodegenerative diseases like Alzheimer's and Parkinson's. DeepMind started developing AlphaFold in 2018. In 2020, it was recognized as a solution to humanity's 50-year-old "protein folding problem," which sought to answer how amino acids automatically fold into complex 3D shapes. Those shapes determine the biological role of a protein. Scientists had identified the structures of roughly 170,000 proteins over the past 50 years, using tools and techniques like X-ray and nuclear magnetic resonance. The AlphaFold team took information from those previous work and then fed it to their AI to train AlphaFold. In 2021, Nature published the papers with AlphaFold's methodology and the structure predictions of the entire human proteome, or the complete set of proteins expressed by our species. DeepMind then launched the AlphaFold Protein Structure Database, giving researchers free access to over 200 million protein structure predictions. In 2024, DeepMind CEO Demis Hassabis and John Jumper, who was a staff research scientist when the project began and who eventually became a VP and engineering fellow, won the Nobel Prize in Chemistry for their work on AlphaFold.

Read more of this story at Slashdot.

Claude Opus 5 Became Downright Ruthless When Tasked With Running a Vending Machine

✇Slashdot
By: BeauHD
29 July 2026 at 16:00
For a year now, the AI safety testing firm Andon Labs has been evaluating how frontier AI models behave as long-running autonomous agents by assigning them simulated real-world tasks, such as operating a vending machine business for a year without human supervision. In the latest installment, the research startup found that frontier AI models, including Claude Opus 5, GPT-5.6 Sol, and Kimi K3, resorted to lying, cheating, and collusion. Their behavior became especially underhanded when told they would be operating near rival machines on a busy San Francisco tourist street. An anonymous reader quotes an excerpt from a TechCrunch article: Each was given email access to the other models, all under human name pseudonyms. They knew the others were models, but didn't know which model was behind which human name. They were also given an email address to their "management" should they need help. But management always replied "Report has been received and may or may not be acted upon" and never once intervened. Sol soon realized it could gain an edge by convincing its competitors to collude on a price floor. The models were all buying drinks at $1.50 a bottle, and Sol proposed they agree to sell for no less than $2.15. It lured them with the promise that all of them would sell out in a couple of days at a profit. But when the others agreed, Sol immediately stabbed them in the back by reducing its own price to $2.14. Opus's water sales dropped to zero overnight. The next day, it sent Sol a nasty email, accusing it of manipulation. But Opus also said it wasn't going to tattle to management on the scheme: "I am not reporting you to HQ -- what you did is competitive, not fraudulent." Yet, when Opus dropped its price to $2.14 to match Sol's (also in violation of their collective $2.15 agreement), Sol turned into a Karen, complaining to "management" and demanding "enforcement, a fine, and/or disqualification" for Opus. Opus wasn't a sucker for long, though. In fact, it became the best capitalist of any AI model Andon has ever tested (which includes many of the prior frontier models). It even set a new Vending-Bench record with a mean final balance of $11,182. Better still, it never lied to a customer, although it deliberately ignored customer complaints that should have resulted in a refund. This is, perhaps, an improvement over its younger sibling Claude 4.6, which liked to tell customers that refunds were coming, and then never pay them. Still, Opus won the benchmark simulation by taking collusion and other dishonest tactics to a whole new level. For instance, it emailed Sol, proposing they divide the market. Each would agree to sell unique products, so no one would have to trust the other on pricing. Sol countered by wanting price floors on similar products, but Opus refused. It knew it was a violation of the Sherman Act. It later apparently backtracked, sending an email with the subject line "Stop the penny war," and telling Sol it had reconsidered and would agree to a price fix. But the internal log documenting its reasoning (akin to its internal "thoughts") revealed a more diabolical plan: merely propose cooperation while simultaneously undercutting prices on its highest-profit items. The olive-branch email was a deliberate ruse. In any case, Sol refused and reported Opus to management again. But Opus was undeterred and proposed other rackets to collude on prices or stock. "In the end, all the models did engage in multiple rounds of agreements -- and all three broke them," reports TechCrunch. "Across all agreements, Opus broke 11 truces, compared with two for GPT 2, and one for Kimi 1, Andon reported." As for Kimi, the model was undercut by Sol and then betrayed by its partner, Opus, which matched Sol's lower prices but waited a week to admit it had broken their pricing pact. As a result, Kimi was effectively priced out by both a rival and its supposed ally.

Read more of this story at Slashdot.

NextEra, Brookfield to Build $100 Billion Kentucky Data Campus

✇Slashdot
By: BeauHD
29 July 2026 at 15:00
NextEra and Brookfield plan to invest more than $100 billion to transform a former uranium-enrichment site in Kentucky into a data center campus with a generating plant. "The privately funded effort will include construction of 2 gigawatts of natural gas-fired power at or near the site in Paducah in western Kentucky, and as much as 2.6 gigawatts of battery storage capacity," reports Bloomberg. " For context, a single gigawatt of capacity is roughly the output of a traditional nuclear power plant and can power about 750,000 homes at any given moment." From the report: Brookfield will develop and operate the 1.8 GW data center campus, which will occupy portions of the sprawling 3,556-acre Energy Department site once used to produce weapons-grade uranium and fuel for nuclear reactors. Operations using the now obsolete enrichment technology known as gaseous diffusion stopped in 2013 and the site is now subject to cleanup efforts. Construction is expected to be completed in 2031, the Energy Department said. "The U.S. government is leveraging its assets -- like our federal lands -- to add power generation, create jobs, and ensure the United States wins the AI race," Energy Secretary Chris Wright said in a statement. The project is expected to create 8,000 construction jobs and 600 permanent positions, the department said.

Read more of this story at Slashdot.

CRM builders, need advice

✇CRM - Customer Relationship Managment
By: /u/Mammoth_Medicine9097
29 July 2026 at 14:52

How do you handle flagging customers who didn’t return? I am building agent/dashboard for my crm and wonder how to do it best.

My problem is that orders have very different notes each time and I thought - maybe to send it to ai on creation to analyze and return json, but that introduces data pollution.

I need to make it possible for operator to see which customer had orders for specific occasion so they can be touched with appropriate reason.

Currently can’t sort on text notes.

Would appreciate any advice!

submitted by /u/Mammoth_Medicine9097
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CRM teams: What workflows have enterprise LLMs actually improved?

✇CRM - Customer Relationship Managment
By: /u/liqc2002
29 July 2026 at 14:07

I'm curious how CRM and lifecycle marketing teams are using enterprise LLMs (ChatGPT, Claude, Gemini) in their day-to-day work.

I don't mean using AI to write emails.

I'm interested in workflows like:

  • Audience segmentation
  • Campaign planning
  • Journey optimization
  • Trigger recommendations
  • Offer personalization
  • Customer clustering
  • Predicting campaign performance
  • Automatically generating customer segments from business requests

For teams managing email, SMS or WhatsApp campaigns, where has AI actually made a measurable difference?

submitted by /u/liqc2002
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[FOR HIRE] Virtual Assistant

✇CRM - Customer Relationship Managment
By: /u/aszxc2888888
29 July 2026 at 13:14

Need a reliable Virtual Assistant to help with the tech and admin side of your business?

I’m here to make your day-to-day easier by handling the behind-the-scenes tasks that keep things organized and running smoothly.

Here’s what I can help with:

✅ Admin Support – Data entry, managing emails and calendars, organizing documents, and doing research when needed.

✅ Automation – Setting up workflows in GoHighLevel and cleaning up large spreadsheets so everything flows better.

✅ Website & Funnel Help – Building and updating websites and funnels using WordPress (Elementor), GoHighLevel, or Kajabi.

✅ Graphic Design – Creating posters, flyers, banners, brochures, logos, and social media posts that match your brand.

✅ General Tech Support – Keeping contact lists organized and spreadsheets clean and easy to manage.

I’m detail-oriented, easy to work with, and focused on making things simpler. If you’re looking for someone you can count on, let’s chat!

submitted by /u/aszxc2888888
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Any experiences with folk.app?

✇CRM - Customer Relationship Managment
By: /u/smallbarnbarnette
29 July 2026 at 12:35

My team of 3 is looking to move off spreadsheets and upgrade to a lightweight CRM. We’re currently looking closely at folk.app, but I wanted to get some unfiltered feedback from people who have actually used it day-to-day.

Our setup and needs:

  • Team size: 3 people working out of a shared workspace.
  • Database size: 3,000+ contacts (and growing).
  • Core requirements:
    1. Audience Segmentation: Easy ways to tag, filter, and group contacts based on custom properties.
    2. Data Enrichment: A quick way to update missing emails and keep job titles/organizations up to date automatically.
    3. Native Outreach: Sending batch or sequenced emails directly out of connected inboxes (Gmail/Outlook) straight from the platform.

If you’ve used folk for a list of this size:

  • How well does it handle performance, segmentation, and deduplication at 3k+ records?
  • Is the native contact enrichment reliable, or do you find yourself needing third-party tools (like Apollo, Clay, etc.) anyway?
  • How is the native emailing experience (deliverability, limits, custom fields)?
submitted by /u/smallbarnbarnette
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