Category: math

But 2024’s “pi day” saw a new announcement…

After successfully breaking the speed record for calculating pi to 100 trillion digits last year, the team at StorageReview has taken it up a notch, revealing all the numbers of Pi up to 105 trillion digits! Spoiler: the 105 trillionth digit of Pi is 6!

Owner and Editor-in-Chief Brian Beeler led the team that used 36 Solidigm SSDs (nearly a petabyte) for their unprecedented capacity and reliability required to store the calculated digits of Pi. Although there is no practical application for this many digits, the exercise underscores the astounding capabilities of modern hardware and an achievement in computational and storage technology…

For an undertaking of this size, which took 75 days, the role of storage cannot be understated. “For the Pi computation, we’re entirely restricted by storage, says Beeler. “Faster CPUs will help accelerate the math, but the limiting factor to many new world records is the amount of local storage in the box. For this run, we’re again leveraging Solidigm D5-P5316 30.72TB SSDs to help us get a little over 1P flash in the system.

“These SSDs are the only reason we could break through the prior records and hit 105 trillion Pi digits.”

“Leveraging a combination of open-source and proprietary software, the team at StorageReview optimized the algorithmic process to fully exploit the hardware’s capabilities, reducing computational time and enhancing efficiency,” Beeler says in the announcement.

There’s a video on YouTubewhere the team discusses their effort.

Currently in beta and only available for this week, there’ll be five of these math puzzles to solve every day. These aren’t one-and-done puzzles like Wordle, and depending on the path you choose to solve one of these math mysteries, you’ll be awarded 1-3 star ratings. If Digits proves to be popular with its readers, the New York Times will then start work on the further development of the game.

Reading scores also declined in more than half the states, continuing a downward trend that had begun even before the pandemic. No state showed sizable improvement in reading. And only about one in three students met proficiency standards, a designation that means students have demonstrated competency and are on track for future success. And for the country’s most vulnerable students, the pandemic has left them even further behind. The drops in their test scores were often more pronounced, and their climbs to proficiency are now that much more daunting.

To discover more efficient matrix math algorithms, DeepMind set up the problem like a single-player game. The company wrote about the process in more detail in a blog post last week. DeepMind then trained AlphaTensor using reinforcement learning to play this fictional math game — similar to how AlphaGo learned to play Go — and it gradually improved over time. Eventually, it rediscovered Strassen’s work and those of other human mathematicians, then it surpassed them, according to DeepMind. In a more complicated example, AlphaTensor discovered a new way to perform 5×5 matrix multiplication in 96 steps (versus 98 for the older method).

This week, Manuel Kauers and Jakob Moosbauer of Johannes Kepler University in Linz, Austria, published a paper claiming they have reduced that count by one, down to 95 multiplications. It’s no coincidence that this apparently record-breaking new algorithm came so quickly because it built off of DeepMind’s work. In their paper, Kauers and Moosbauer write, “This solution was obtained from the scheme of [DeepMind’s researchers] by applying a sequence of transformations leading to a scheme from which one multiplication could be eliminated.”

Social media users were largely amused by the illustrations, but many also criticized them as bringing disrepute and “cultural annihilation” to China, speculating they were the deliberate work of western infiltrators in the education sector. Related hashtags were viewed billions of times, embarrassing the Communist party and education authorities who announced a review of all textbooks “to ensure that the textbooks adhere to the correct political direction and value orientation.”

In a lengthy statement released on Monday, the education authorities said 27 individuals were found to have “neglected their duties and responsibilities” and were punished, including the president of the publishing house, who was given formal demerits, which can affect a party member’s standing and future employment. The editor-in-chief and the head of the maths department editing office were also given demerits and dismissed from their roles. The statement said the illustrators and designers were “dealt with accordingly” but did not give details. They and their studios would no longer be engaged to work on textbook design or related work, it said. The highly critical statement found a litany of issues with the books, including critiquing the size, quantity and quality of illustrations, some of which had “scientific and normative problems.”

The Linux kernel’s random number generator has seen its first set of major improvements in over a decade, improving everything from the cryptography to the interface used. Not only does it finally retire SHA-1 in favor of BLAKE2s [in Linux kernel 5.17], but it also at long last unites ‘/dev/random’ and ‘/dev/urandom’ [in the upcoming Linux kernel 5.18], finally ending years of Slashdot banter and debate:

The most significant outward-facing change is that /dev/random and /dev/urandom are now exactly the same thing, with no differences between them at all, thanks to their unification in random: block in /dev/urandom. This removes a significant age-old crypto footgun, already accomplished by other operating systems eons ago. […] The upshot is that every Internet message board disagreement on /dev/random versus /dev/urandom has now been resolved by making everybody simultaneously right! Now, for the first time, these are both the right choice to make, in addition to getrandom(0); they all return the same bytes with the same semantics. There are only right choices.

Phoronix adds:
One exciting change to also note is the getrandom() system call may be a hell of a lot faster with the new kernel. The getrandom() call for obtaining random bytes is yielding much faster performance with the latest code in development. Intel’s kernel test robot is seeing an 8450% improvement with the stress-ng getrandom() benchmark. Yes, an 8450% improvement.