Lawrence Person's BattleSwarm Blog

U.S. Supreme Court Justice Samuel Alito issued an administrative stay of Tuesday’s ruling by an El Paso panel of federal judges that rendered the new congressional map passed by Texas Republicans this summer unusable for the 2026 midterm election.

The order restored the new map, pending consideration of the appeal by the State of Texas, and directed the Democratic-aligned parties to submit their response by Monday.

Snip.

The ruling drew a particularly pointed dissent from Judge Jerry Smith, the lone dissenter on the panel, who asserted that the motivation behind the redraw was clearly partisan gain — a position that sits outside the jurisdiction of the court.

Following that ruling, Attorney General Ken Paxton appealed the ruling to the U.S. Supreme Court on Friday, asking for an administrative stay — which Alito granted.

“Compounding the harm, the district court entered its sweeping injunction far too late in the day — ten days after Texas’s candidate filing period had already opened. The injunction changes the boundaries of all but one of the State’s 38 congressional districts, enjoining Texas from using its duly enacted 2025 map and resurrecting the repealed 2021 map,” Texas wrote in its appeal.

“The chaos caused by such an injunction is obvious: campaigning had already begun, candidates had already gathered signatures and filed applications to appear on the ballot under the 2025 map, and early voting for the March 3, 2026, primary was only 91 days away. The lateness of the district court’s injunction (issued 38 days after the hearing) alone warrants a stay.”

As things stand, Texas Republicans’ map is back in effect while the U.S. Supreme Court considers the case in expedited fashion.

Texas’ candidate filing deadline is December 8, 2025.

There are thousands of accounts like this. Many of them explicitly claim to be American or Western, but are run by random people in Asia and Africa to sow chaos and get clicks.

BREAKING – Waves of Democrat influencers are being exposed as foreigners under X’s new location update, including leftist X agitator Alex Cole, who claimed he voted for Kamala but has now been revealed to be Canadian. pic.twitter.com/3LrAsYCiMw

— Right Angle News Network (@Rightanglenews) November 22, 2025

And a whole lot of “besieged Gazans” turn out to be posting from Europe…

Temporary Protected Status (TPS) is supposed to be used in extreme cases of humanitarian need for short terms (usually for 6, 12, or 18 months), allowing foreign refugees a safe haven in America.

As deportation efforts have ramped up, however, the American public has learned that some foreigners have remained in the country on TPS for decades. Some politicians and businesses have purposely imported large numbers of foreigners into small American towns, such as Haitians in Ohio and Pennsylvania, as cheap labor to replace Americans.

Faster, please.

President Donald Trump’s initiative to eliminate government waste and fraud through a Department of Government Efficiency (DOGE) has quietly disbanded with a full 8 months still left on its charter.

Earlier this month when Reuters asked Office of Personnel Management Director Scott Kupor about the status of DOGE, Kupor replied, “That doesn’t exist.”

Representative Tim Burchett (R-TN) said that Elon Musk, who headed up the DOGE effort, was pushed out Washington D.C. because he was getting too close to exposing corrupt officials who are enriching themselves through dark money non-governmental organizations (NGOs).

Burchett told Benny Johnson, “NGO money pours into Washington and ends up in politicians’ pockets as dark money.”

DOGE had made dramatic impact on the federal government during the early months of Trump’s second term, shrinking the size of federal agencies and cutting their budgets or revealing astonishing amounts of questionable money flowing through NGO coffers.

Sound like a good reason to continue the work, not abandon it…

The Philippine Navy recently caught Chinese Fishing Militia putting Cyanide in the water near the BRP Sierra Madre at the Second Thomas Shoal.

The incident that was recorded on camera demonstrates the brutality & destruction meted out by the Chinese Fishing Militia inside… pic.twitter.com/L7NCI0UIik

— Isabella Anderson (@IsabellaAn67) November 27, 2025

The apparent reason Armata failed is this: sanctions.

But there’s more to the story, too. In fact, several interlocking factors account for the T-14’s failure to materialize as intended.

Let’s first look at costs and priorities: the unit cost of the T-14 was estimated at several million dollars – far higher than Russia had budgeted for.

The increase in cost meant that it couldn’t actually be sustained at scale. And, faced with heavy losses in Ukraine and urgent demands to ramp up numbers, Moscow opted to modernize its legacy platforms, such as the T-90, rather than invest in an expensive and unproven system. A tough choice, but a logical one.

The domestic production line for the T-14 never actually achieved accurate serial output, in large part thanks to sanctions and industrial bottlenecks.

There was no assembly line. Yes, really: every vehicle was hand-built like a luxury car. Sanctions and supply-chain constraints further hindered the manufacture of key components and high-end electronics required for the platform.

But even if Russia had been able to assemble more of the tanks before the sanctions really kicked in, it might not have changed the reality on the battlefield. Even when the war in Ukraine created a burning need for armored vehicles, Russia hesitated to commit T-14 units to the frontline for one worrying reason: they were vulnerable.

With the rise of automated systems, drone warfare, and long-range combat, those tanks may have proven as vulnerable as older units – and losing tanks built pre-sanctions would mean replacing them with older tanks.

That wouldn’t have made sense.

For more than a decade, the T-14 Armata has embodied Russia’s ambition to leap ahead of the West in tank design and warfare.

But it failed.

Brown County Judge Shane Britton was suspended from office without pay on Tuesday, one day after he was arrested on multiple charges that included allegations he assaulted a female prosecutor and interfered with the prosecution of a family violence case.

According to indictments handed down by a grand jury last week, Britton has been charged with three felonies: tampering with a witness in a family violence case, assault of a public servant, and tampering with a government document.

Britton is a Republican.

To understand the difference, it helps to look at what each chip was originally built to do. A GPU is a “general-purpose” parallel processor, while a TPU is a “domain-specific” architecture.

The GPUs were designed for graphics. They excel at parallel processing (doing many things at once), which is great for AI. However, because they are designed to handle everything from video game textures to scientific simulations, they carry “architectural baggage.” They spend significant energy and chip area on complex tasks like caching, branch prediction, and managing independent threads.

A TPU, on the other hand, strips away all that baggage. It has no hardware for rasterization or texture mapping. Instead, it uses a unique architecture called a Systolic Array.

The “Systolic Array” is the key differentiator. In a standard CPU or GPU, the chip moves data back and forth between the memory and the computing units for every calculation. This constant shuffling creates a bottleneck (the Von Neumann bottleneck).

In a TPU’s systolic array, data flows through the chip like blood through a heart (hence “systolic”).

• It loads data (weights) once.
• It passes inputs through a massive grid of multipliers.
• The data is passed directly to the next unit in the array without writing back to memory.

What this means, in essence, is that a TPU, because of its systolic array, drastically reduces the number of memory reads and writes required from HBM. As a result, the TPU can spend its cycles computing rather than waiting for data.

Google’s new TPU design, also called Ironwood also addressed some of the key areas where a TPU was lacking:

• They enhanced the SparseCore for efficiently handling large embeddings (good for recommendation systems and LLMs)
• It increased HBM capacity and bandwidth (up to 192 GB per chip). For a better understanding, Nvidia’s Blackwell B200 has 192GB per chip, while Blackwell Ultra, also known as the B300, has 288 GB per chip.
• Improved the Inter-Chip Interconnect (ICI) for linking thousands of chips into massive clusters, also called TPU Pods (needed for AI training as well as some time test compute inference workloads). When it comes to ICI, it is important to note that it is very performant with a Peak Bandwidth of 1.2 TB/s vs Blackwell NVLink 5 at 1.8 TB/s. But Google’s ICI, together with its specialized compiler and software stack, still delivers superior performance on some specific AI tasks.

The key thing to understand is that because the TPU doesn’t need to decode complex instructions or constantly access memory, it can deliver significantly higher Operations Per Joule.

“TPU v6 is 60-65% more efficient than GPUs.”

Happy Thanksgiving 🫡 🦅 pic.twitter.com/yhJYbrCQZx

— Kristi Yamaguccimane (@TheWapplehouse) November 27, 2025

(Hat tip: Ace of Spades HQ.)