I really liked the fact that you can share a PowerPoint presentation as an object rather than an image of the screen. This allows the presenter to see their notes and future slides, while the viewers can flip back and forth between slides and maybe zoom in on details.

But this has aspects of monopolist behavior (using the Office monopoly to support entry into videoconferencing). I wonder if the EU will require Microsoft to create free libraries or APIs for other video conferencing software to do this?

For 20 years, plus or minus, personal computers reversed that idea.

I once wrote a 6808 assembler in Microsoft Excel (to put a scrolling message on a Heathkit ET-3400 I found in the lab). I don't think it would take much more to write one for the 6502.

It's nice to see this. I expect it's like a visit from an old friend for many people on slashdot.

I got my start with computers on the Commodore PET in our middle-school lunchroom, taking apart commercial BASIC programs, changing them to do what I wanted and saving my creations to blank parts at the end of the cassette tape. Then I moved on to summer BASIC classes on a TRS-80 and eventually more serious programming in Applesoft BASIC on an Apple ][+ as a teenager.

Never realized all those BASICs were more or less the same program from Microsoft.

Anopheles mosquitoes only spend abut 2% of their time interested in biting humans (only adult females, for a few hours every few days). So potentially they are doing other important things in the ecosystem the rest of the time. As larvae, they are important filter feeders and food sources in shallow water ecosystems. As adults, they are pollinators and also convert plant sugars into food for bats, birds, frogs, spiders, dragonflies, etc.

On the other hand, one species, Anopheles gambiae, strongly prefers humans over other species, albeit for only a small part of the time. They get over 95% of their blood meals from humans in some villages and are a major vector for malaria. It seems like it might be OK to extirpate a species that cannot live without preying on humans and causes huge harm in the process.

The Python program has minimal error handling, just using the built-in behavior. It's almost exactly equivalent to the explicit error handling from the C++ version, e.g.,

std::cerr << "Failed to open data.parquet: " << infile_result.status().ToString() << "\n";
return 1;

As I'm saying, for data science workflows, Python can give similar performance and behavior to C++, with code that is easier to write and understand. So some people opt for Python.

The built-in Python error handling is pretty equivalent to the explicit handling in the C++ program: file not found, missing column a, etc.

I picked parquet because I see it a lot for data science workflows. If youâ(TM)d rather use csv, just change âparquetâ(TM) to âcsvâ(TM) in the Python code and drop the âoeengineâ argument (itâ(TM)s not actually needed anyway). I doubt the change would be so simple in the C++ code, or that you would end up with a C++ program as easy to write, debug or share as the Python one.

But by all means, use C++ if it works for you. I was just showing why others might choose Python.

I gave all my Apple wealth away because wealth and power are not what I live for. I have a lot of fun and happiness. I funded a lot of important museums and arts groups in San Jose, the city of my birth, and they named a street after me for being good. I now speak publicly and have risen to the top. I have no idea how much I have but after speaking for 20 years it might be $10M plus a couple of homes. I never look for any type of tax dodge. I earn money from my labor and pay something like 55% combined tax on it. I am the happiest person ever. Life to me was never about accomplishment, but about Happiness, which is Smiles minus Frowns. I developed these philosophies when I was 18-20 years old and I never sold out.

Both of the programs below will read columns a and b from a parquet file, multiply them elementwise using vectorized operations, and save the original columns plus the new one to a new parquet file. For large datasets, the Python or C++ versions will take equally long to run. But the Python one is much faster to write and debug and easier for partners to understand. The dependency installation process will also be identical across platforms for the Python version. That is why people use Python for data science.

Python version:

import pandas as pd
df = pd.read_parquet("data.parquet", engine="pyarrow")
df["c"] = df["a"] * df["b"]
df[["a", "b", "c"]].to_parquet("output.parquet", index=False, engine="pyarrow")

C++ version (with some extra-long lines and extra spaces to keep slashcode happy):

#include <iostream>
#include <memory>
 
#include <arrow/api.h>
#include <arrow/compute/api.h>
#include <arrow/io/api.h>
#include <parquet/arrow/reader.h>
#include <parquet/arrow/writer.h>
 
using arrow::Status;
 
int main() {
// Open input Parquet
  auto infile_result = arrow::io::ReadableFile::Open("data.parquet");
  if (!infile_result.ok()) {
    std::cerr << "Failed to open data.parquet: " << infile_result.status().ToString() << "\n";
    return 1;
  }
  std::shared_ptr<arrow::io::ReadableFile> infile = *infile_result;
 
// Read as Arrow Table
  std::unique_ptr<parquet::arrow::FileReader> reader;
  auto st = parquet::arrow::OpenFile(infile, arrow::default_memory_pool(), &reader);
  if (!st.ok()) { std::cerr << st.ToString() << "\n"; return 1; }
 
  std::shared_ptr<arrow::Table> table; st = reader->ReadTable(&table);
  if (!st.ok()) { std::cerr << st.ToString() << "\n"; return 1; }
 
// Fetch columns a and b
  auto a_col = table->GetColumnByName("a"); auto b_col = table->GetColumnByName("b");
  if (!a_col || !b_col) {
    std::cerr << "Input must contain float columns named 'a' and 'b'.\n";
    return 1;
  }
 
// Ensure float64 and compute c = a * b using Arrow's vectorized kernels
  auto f64 = arrow::float64();
  auto a_cast_res = arrow::compute::Cast (arrow::Datum(a_col), f64);
  auto b_cast_res = arrow::compute::Cast (arrow::Datum(b_col), f64);
  if (!a_cast_res.ok() || !b_cast_res.ok()) {
    std::cerr << "Failed to cast columns to float64.\n"; return 1;
  }
  arrow::Datum a64 = *a_cast_res; arrow::Datum b64 = *b_cast_res;
 
  auto mult_res = arrow::compute::CallFunction("multiply", {a64, b64});
  if (!mult_res.ok()) { std::cerr << "Multiply failed: " << mult_res.status().ToString() << "\n"; return 1; }
  arrow::Datum c = *mult_res;
 
// Build output table (a, b, c)
  auto schema = arrow::schema({
    arrow::field("a", f64), arrow::field("b", f64), arrow::field("c", f64)
  });
 
  auto out_table = arrow::Table::Make(
      schema, {a64.chunked_array(), b64.chunked_array(), c.chunked_array()}
  );
 
// Write Parquet
  auto outfile_result = arrow::io::FileOutputStream::Open("output.parquet");
  if (!outfile_result.ok()) {
    std::cerr << "Failed to open output.parquet for writing: " << outfile_result.status().ToString() << "\n";
    return 1;
  }
  std::shared_ptr<arrow::io::OutputStream> outfile = *outfile_result;
 
  st = parquet::arrow::WriteTable(*out_table, arrow::default_memory_pool(), outfile, /*chunk_size=*/1024);
  if (!st.ok()) { std::cerr << "WriteTable failed: " << st.ToString() << "\n"; return 1; }
 
  return 0;
}

I'm very happy with where Iâ(TM)ve reached in my career, but I've mainly used stuff that I learned on my own for BA and PhD theses, or learned on the job. I loved college and grad school and made some great friends, who are now also doing well and great to work with when I get a chance.

Iâ(TM)m not saying you shouldnâ(TM)t pay attention in class. Working hard got me into a good grad school and a good post-doc, and those have opened doors for me. Thatâ(TM)s what I meant by the stamp of a high achiever. I also learned a lot in my classes, although more from reading, thinking and writing than from listening to lectures. But only a few classes have proven to be valuable long term.

So I stand by my point - what you learn in lectures is only a small part of the long-term value of attending grad school.

Little do you know that you'll be going out into a world designed in the 2010s or - gasp! - even earlier, when you are done.

You also haven't learned yet that nothing your professor says in school will matter. You'll learn a bit from the books and assignments on your own, but what really matters will be the connections you make and the stamp on your resume that says "certified achiever". Actual job skills - you'll learn on the job.

If the user does a Google search for "Microsoft support", sees an ad linking to microsoft.com that says "Contact 1-800-123-4567 for support", clicks through to the Microsoft page, checks that the URL is really https://microsoft.com/ and the top of the page says "Call 1-800-123-4567 for support" (and the rest of the page is a list of less-helpful support options, whatever Microsoft throws up when searching for "Call 1-800-123-4567 for support"), then it would be pretty easy for them to fall for this scam.

No, it requires them to do a Google search for the company or their problem, then shows an ad with a link to the legitimate company's website, then shows a "tech support" number to call on the real company's website. This is a pretty easy scam to fall for, for anyone in a hurry.

The original ArsTechnica article (but not TFS or TFA) shows that this works by creating a standard get-style search on the company website, which then shows the scammer's search terms nice and clearly at the top (e.g., "Call 1-800-123-4567 for support"). On sites that remove as many frills as possible, the search terms can look a lot like part of the site, especially if the user didn't type them themself.

I would assume the risk is someone taking a payment from your physical credit card through your pocket/wallet. But I donâ(TM)t know if the new standard changes the cards or just the minimum distance the reader must be able to reach. If the latter, then there really wouldn't be any effect on security.

I don't know why voltage was running high (requiring generators to absorb reactive power), but from REDâ(TM)s announcements, it clearly was. It was a light load day, so one factor could be the Ferrenti effect, which drives up voltage on lightly loaded lines. There should be more details in the report that was published today, but I havenâ(TM)t seen a copy.