DROP Service Interim Update

Earlier this year, I wrote about how your can protect your privacy using California’s Delete Request and Opt-out Platform (DROP) service. DROP launched on January 1, 2026, and data brokers began processing requests on August 1, 2026. Given that data brokers are required to delete data within 45 days of receiving a request, I wanted to see how things were coming along at day 29. Here are my current stats, as reported on my DROP account:

And here is the DROP website’s glossary of deletion statuses:

When browsing the full list of data brokers, I see this:

Unfortunately there are 66 pages to scroll through on my account, and there does not appear to be a way to export the full list of data brokers along with my request statuses. It would be nice for them to add that feature later.

The DROP website provides the following information: “Data brokers will begin accessing DROP soon. Processing becomes mandatory beginning August 1, 2026, but status updates can take up to 90 days to appear in DROP depending on data broker workflows. Your status for each data broker will update once your request is processed.” My interpretation is that either (1) a majority of data brokers (490 out of 656) have not processed my deletion request yet and/or (2) some of those 490 data brokers have actually processed my deletion request, but the statuses have not yet been updated in DROP due to data broker workflows.

While the DROP website says, “Under law, data brokers have 45 days to delete your data after they receive your request,” it seems hard to determine if the law has been broken if the statuses can take 90 days to be updated. In the worst case scenario, a data broker could delete my data on day 45, and then it could take up to 90 days to update the DROP website, so that would be 135 days after August 1 which would be December 14, 2026. Maybe I’ll check back again toward the end of the year to see how well data brokers are complying with DROP requests.

University of California Acceptance Rate Data

If you have a high school senior who is getting ready to apply to University of California schools, you may have seen acceptance rate statistics such as the ones from Money Magazine a few months ago which I wrote about in my “LLM Analysis of College Ratings” blog. For convenience, I am re-posting the graphic here.

The acceptance rate statistics are from a nationwide sample, but what if I told you that you could look up University of California acceptance rate statistics for students at a specific high school? The University of California Information Center publishes data on Admissions by Source School and segments data into several subcategories as shown here:

The data tables show applicants, admissions, and enrollments by California high schools and community colleges for freshmen and transfer entrants by source school, mean GPA, ethnicity and school. Of particular interest might be “Single high school lookup” under the “Freshman admission by source high school” section. Data tables are provided for:

• Counts of fall freshmen by race/ethnicity
• Counts of fall freshmen by gender
• Average freshman GPA

After clicking on any of these 3 options, you will need to enter the high school name in the “Search for school name” field. Depending on the name of your school, the exact high school name could be tricky to find. If you come up blank, then go back to the home page and click on any of the 3 options under Freshman admission by source high school > All source high schools. Then filter by city and/or county and browse for the name of the high school of interest.

Back to the “Single high school lookup” section… After selecting a data table for counts by race/ethnicity, gender, or GPA, you will have the option to filter by year. You’ll also see breakdowns by campus, fall term, and applications/admissions/enrollment.

If you prefer to sort and filter data in Excel like I do, you’re in luck because there is a download button that gives you the option to download as an image, data, cross tab, PDF, or PowerPoint. Selecting “data” will result in the download of a .csv file which you can then play with in your favorite spreadsheet or database application.

I found this data to be useful because although the national acceptance rate statistics are good to know, being able to see acceptance rate statistics from my child’s high school provided a slightly different perspective. I hope you’ll find it as useful as I did. And if you found this data interesting, there are plenty of other data tables to explore at the University of California Information Center.

Citi Costco Visa Identity Verification

Last year our family visited several Asian countries, and we managed to get by with eSIM data-only plans. The only setbacks occurred when our Citi Costco Visa card flagged some transactions as suspicious (which I wrote about here and here), and because Citi attempted to notify me via voice and SMS text—which we did not receive—it prevented our purchases from being made. This year, I made sure to add my Google Voice number to my Citi Costco Visa card in hopes that I would be given an option to verify transactions using a data-only eSIM plan. It worked. When making a transaction, I was presented with the following options for identity verification:

You may have noticed that there were options to call or text me at the …2505 number, the the only option for the …2516 (Google Voice) number was to call me. I am not certain, but my phone contact information on the Citi website are:

• Home Number: …2505  → I think Citi uses this for calls
• Primary Mobile: …2505  → I think Citi uses this for text messages
• Alerts Mobile: …2516  → I think Citi uses this for calls

If my assumptions above are correct, then I think Citi should also present an option to send text messages to the alerts mobile number. While calling me at my Google Voice number worked for identity verification, I would have preferred getting a text message at my Google Voice number so I could copy and paste the code.

In any case, if you have a Google Voice or another VoIP (Voice over Internet Protocol) service, consider adding that contact number to your Citi card so that you can easily verify your identity using data-only eSIM plans when traveling abroad. I assume that this approach may work for other credit cards, but you’ll need to review your options and/or ask customer support.

EV Recommendations to Car Rental Companies

I have recently experienced several suboptimal car rentals which I’ve written about in this series. While traveling this week, I booked a rental car with Budget. The best deals were with electric vehicles (EVs), and given that I am comfortable with driving EVs and charging EVs at the company apartment, I chose an EV.

Upon vehicle pickup, I learned that Budget no longer provides charging cables. However, I discovered this in a circuitous manner. I recalled a prior experience in which I was given an EV with a low battery and without a charging cable. Therefore, I made sure to search my rental car for a charging cable—it didn’t have one. So I went back to the rental counter, and they assigned a different EV to me—that one didn’t have a charging cable either. I was then told by the manager that Budget no longer provides charging cables “because people steal them”. For context, not all car rental companies have this policy. Just last week, a co-worker rented an EV from another company, and it provided a charging cable.

When I rent EVs for my business trips to company headquarters, I always charge them at the company apartment which has electrical outlets in the 2-car garage, and for that I need a charging cable. The great benefit is that no time is lost by simply plugging in the car at the apartment. The alternative is to charge the vehicle at a public charging station which is undesirable for me because a typical level 2 public charger can take several hours to charge an EV from 50% to 80% capacity. So if a car rental company does not provide a charging cable along with an EV rental, that significantly worsens the customer experience.

I ended up switching from an EV to a hybrid vehicle, and I had a flawless experience with it. That being said, I have a few recommendations to all car rental companies who rent EVs to their customers.

First, car rental companies have a responsibility provide charging cables with EV rentals. Not every customer is willing or able to spend hours of precious time at a charging station. Business travelers are busy. Leisure travelers want to maximize their time on vacation. Nobody wants to use a public charging station unless it is their last option. Plugging an EV into a standard outlet is much slower than a level 2 charging station, but if it can be left unattended (e.g., while sleeping), the convenience far outweighs the slower charging speed. A charging cable should be considered a standard item included in an EV rental.

Second, charge the customer if they do not return the charging cable. If a customer borrows a GPS or a child car seat and fails to return it, then I assume the customer would be charged for those items. A car rental company should do the same for charging cables, and I would completely understand if the replacement fee for a charging cable exceeded the cost of a brand new charging cable because of the effort that must be taken to manage an inventory of charging cables. Furthermore, car rental companies already place a temporary charge on the customer’s credit card (Budget charged me $250 for this week’s rental), so they are already pre-authorized to charge fees for lost or stolen charging cables.

Third, charge the EV to 80% before letting a customer borrow it. This is a common customer expectation. It is also a common expectation that vehicles are adequately prepared for rental. The tire pressure should be adequate, the headlights should be working, none of the warning lights should be flashing, and the vehicle should be free of trash from the prior rental. Most car rental companies that I’ve used also require that the car be returned with at least 70% (or similar) charge, or a fee will be incurred (similar to a refueling fee for gas vehicles). On the flip side, car rental companies have a duty to provide customers with EVs whose batteries are 70-80% charged.

If a rental company cannot support EV rentals with the same level of convenience and preparedness that customers expect from gasoline vehicles, it shouldn’t offer them.

LLM Analysis of College Ratings

Money Magazine recently published research on the best colleges in America. Its methodology includes metrics that are weighted based on graduation rates, costs, financial aid, student debt, and alumni salaries. My daughter is looking at University of California schools (among other options), and I noticed that while UC Berkeley, UC Davis, UC Irvine, and UC San Diego achieved 5-star ratings, UCLA “only” received 4.5 stars.

Beyond what was stated in the methodology, I could not find detailed information about the raw scores that led to the star ratings, so I decided to consult various large language models (LLMs) to see if they could do some digging for me and propose plausible explanations for why UCLA wasn’t given a full 5 stars as I would have expected.

I asked the exact same question to Copilot, ChatGPT, and Claude: “Money Magazine released their 2026 ratings of the best colleges in the US (https://money.com/best-colleges/). Try your best to find out why UC Berkeley, UC Davis, UC Irvine, and UC San Diego achieved 5-star ratings while UCLA only received 4.5 stars. Make sure to examing their scoring methodology and determine what criteria may have caused UCLA to not achieve a full 5 stars.” Note that I copied and pasted the same typo (“examing” should have been “examine”).

Copilot didn’t spend much time researching this topic, and it started spitting out an answer 1-2 seconds after I pressed the “return” key. One of its main explanations for UCLA not achieving 5 stars was due to affordability which didn’t make sense based on the table above, so I followed up with a 2nd prompt: “UC Berkeley has a higher estimated full price and estimated priced with average aid than UCLA, yet UC Berkeley achieved 5 stars. Are you still confident in your assessment? If not sure, then state so.” Copilot then backtracked and revised its explanation, and its revision sounded more plausible to me. Here is Copilot’s full response.

A similar thing happened with ChatGPT which spent only a second or two longer to “think” than Copilot, and it responded almost immediately. It too explained that cost was a factor in it not achieving 5 stars, so I followed up with the exact same 2nd prompt: “UC Berkeley has a higher estimated full price and estimated priced with average aid than UCLA, yet UC Berkeley achieved 5 stars. Are you still confident in your assessment? If not sure, then state so.” Like Copilot, ChatGPT also backtracked and revised its explanation. Here is ChatGPT’s full response.

On the other hand, Claude thought long and hard about its response. It displayed multiple websites that it was consulting to formulate its response, including Money Magazine’s methodology page and the websites from each of the schools mentioned. I can no longer see the pages it was consulting, as they disappeared and were not displaying in the final response. Although I didn’t use a stopwatch, I’d estimate that Claude took 20-30 seconds to think before providing a response. I felt that Claude’s explanation was the most analytical and credible of the 3 LLMs, and unlike Copilot and ChatGPT, I didn’t feel that any of its responses were contradicted by the data. Here is Claude’s full response.

Of course, these are my personal opinions which are completely subjective. Also, my conclusion that Claude performed the best on this specific task are not necessarily generalizable to conversations about other subjects. The take home message is that if you often consult LLMs, I’d encourage you to always think critically about LLM replies and to explore multiple LLMs to compare and contrast their responses and determine which ones are best suited to your needs.

3D Model License Violation

I contribute 3D models to the 3D printing community on MakerWorld, the Bambu Lab model repository. One of the models that I uploaded was an iPad stand for thick cases, and it is the model in my collection that gets downloaded and printed the most. Recently a stranger messaged me to let me know that Sarina’s 3D Printing was selling my model on Facebook. This was Sarina’s post:

The problem with Sarina’s post is that I had uploaded the iPad stand under a Creative Commons Attribution-NonCommercial 4.0 International Deed (CC BY-NC 4.0) license which means that the model cannot be sold without my permission. So I decided to write a comment on Sarina’s post: “Just so everyone knows, the original model is available at https://makerworld.com/en/models/985191-stand-for-ipad-with-thick-case, and it is provided to the community under an Attribution-NonCommercial license which means that work must be attributed to the original designer, and the object cannot be sold.”

Within a couple of days, the post had been taken down. Unfortunately it is very common for people to violate Creative Commons license terms. Sometimes it is blatant theft, such as these examples:

• Pistol Hanger
• Wheel Stand
• And many more examples

Because I am only a 3D printing hobbyist, and I don’t depend on 3D printing for income, unapproved use of my models does not impact me financially. If anything, I choose the view the breach of licensing terms of my 3D model as a compliment. However, there are many designers out there whose models are used without their permission.

I greatly appreciate being notified by a stranger that someone was selling my model. I recently noticed some suspicious activity and took similar action. A designer posted AirPods Max Jewelry under a Cults 3D Private Use License which prohibits commercial sale, remixing for public sharing, and distribution. However, the exact same model was reposted as Airpods Max Skeleton Accessory. I publicly commented on the repost and also messaged the original designer.

I’ve found the 3D printing community to be helpful and supportive of one another, although there are occasional bad actors. If we all look out for each other, we can hopefully hold people accountable to the licenses that make this community possible.

Image Editing with LLMs

Yes, you read that correctly. Large language models (LLMs) can come in handy for not just text and image generation—they can be versatile image editors too. Perhaps you’ve uploaded a photo of yourself to your favorite LLM and asked it to generate a caricature of you or portrayed you as a celebrity being chased by paparazzi. These are LLM-based examples of image editing in which you start with an image, add your text-based prompt to manipulate the image, and the result will hopefully resemble what you had in mind.

I recently came up with another use case for image editing. I was trying to find a high quality image of the Eagles’ Hotel California album cover. I searched the web and found many photos and scans of the album cover, but they all had one major shortcoming—the dark areas in the bottom half of the image had little to no detail. Here are 2 such examples:

I uploaded the images to both Copilot and ChatGPT and entered the following prompt: “These are 2 photos of the cover of the Eagles "Hotel California" album with different exposures and levels of detail in the shadows. Merge them into 1 photo and recover details from the shadows. Significantly boost the shadows so that it is possible to see the trees and bushes. Preserve the fluorescent "Hotel California" words that are superimposed on what looks like a car's side view mirror. Also boost the fluorescent "Hotel California" words so they are more bold. Preserve the original aspect ratio. Reduce overall contrast by making the sky a warmer golden glow and increase overall brightness, especially in the darker shadows.” I got very similar results with both Copilot and ChatGPT, and here is the result from the latter:

As you can see, ChatGPT did a remarkable job of creating the bushes in the lower half of the album cover. I honestly don’t know if it was able to recover detail from the source images or if it generated the bushes from scratch (or perhaps a combination of both). In any case, I was very happy with the recovery of what was otherwise lost detail. It also slightly sharpened the palm trees and did a very nice job of highlighting the “Hotel California” stylized wording while preserving its original look and feel. This was exactly the kind of image quality I had hoped to find in a Hotel California album cover, and although I was unsuccessful with my search, I was thrilled to learn that LLMs could generate the next best thing.

If you’re wondering why I wanted such an image, it’s because I wanted to 3D print the Hotel California album cover, and I wanted to include some detail in the bottom half rather than have it appear pure black. Here is the resultant 3D print:

If you have a 3D printer, you can access the 3D model and print profiles here. I hope this give you ideas for how you can use LLMs to edit photos.