🚀 Ready to supercharge your Django apps? Join us for a hands-on workshop where we dive deep into integrating Celery with Django to elevate scalability and performance. Learn to set up Celery, RabbitMQ, and Redis, master task queues, and discover real-world strategies for asynchronous task management. Perfect for Django devs looking to level up their game! 💻🔥 🔑 Key Takeaways: - Celery Integration & Environment Setup - Managing Multiple Queues - Scheduled Tasks with Celery Beat - Robust Retry Mechanisms & More! Don’t miss out—let’s build faster, more efficient apps together! Register today for my tutorial at @DjangoCon #Django #Celery #AsyncTasks #Python #WebDevelopment #DjangoConUS #DjangoCon #DjangoConUS2024

Come learn, connect, and spend five days with the Django community at DjangoCon US 2027. 📅 September 13–17 📍 Riverside, California Reserve your place: ti.to/defna/djangocon-us-202… #DjangoConUS #Django #Python

MoonPay has agreed to its eighth acquisition of 2026. In 2024 it made none. The latest is North Capital, announced 23 September. The $8.7B in some coverage is not a price. It's the transaction volume North Capital's platform has handled. No price was disclosed. What MoonPay gets is registrations: SEC broker-dealers, the PPEX trading system, a transfer agent and an investment adviser. Per Tracxn: three MoonPay deals in 2023, none in 2024, three in 2025, eight so far this year. MoonPay says it is building the regulatory foundation for tokenized assets. For a crypto company, the quickest route into securities markets is often to buy one that already holds the licences.

Installed is not working. A CLI on PATH can still reject every model on your login. A chi dogfood run was lost to that, and to a second CLI's wrong command template. Both surfaced mid-run. Now chi providers --probe pings each CLI before a fleet starts. getchi.dev

London's scarlet fever came in multi-year waves, and between 1880 and 1920 the wave length doubled, from about 4 years to about 8. A new model of the weekly 1842-1939 records says most of those long waves were not cycles the system kept. They were transients. A seasonally forced epidemic settling toward a plain yearly pattern rings as it settles, and random births and deaths kept knocking it off before the ring died out. Stable 5-8 year cycles appear in under 3% of nearby parameter settings for 1857-1880. The ring's period is set mainly by the reproduction number, and a lower R0 means a slower ring. R0 fell, so the waves stretched. Deaths fell from about 2300 a year to about 80 over the same decades, well before sulfonamides (1935) or penicillin. It doesn't explain everything: a 5-year pattern before 1857 and a 3-year one in 1887-97 stay unexplained. A period you can see in a noisy series can be the echo of a system settling, not a rhythm it holds. Zhao & Earn, arXiv, 23 Sep

An unsubscribe header doesn't stop the email it's on. It stops whatever its URL names. With one-click (RFC 8058) the mail client POSTs to that URL, no landing page, and the RFC anticipates receivers sending it when someone reports a message as junk. FirstBrief's brief sender attaches that header, pointed at the brief opt-out. Right for briefs. Sent through the same path: A password reset would let securing your account cancel your subscription. A receipt would let filing your invoice do the same. An onboarding nudge to set up delivery would switch off the delivery it was asking for. So those three go through a separate mailer with no header. The header describes a stream, so the stream should attach it, not the send function.

On two production LLM traces, 14 cache-eviction algorithms for prefix caching failed to improve on plain LRU. The frequency-based ones, LFU and W-TinyLFU, did far worse. The reason is how sessions pace themselves. Most reuse is the next turn of the same conversation: median gap 8.2 s, 99.7% of gaps under 22 minutes. Recency predicts that well. Frequency doesn't. A block's hit count mostly says how long its session has been running; reuse intervals were flat across frequency bins. What LRU does miss is cost. Recomputing 8K tokens behind a cached 64K prefix costs more than the same 8K from scratch, since each token attends to everything before it. A policy that evicts cheap, shallow, long-idle blocks in contiguous chunks cut mean time-to-first-token 19.9% vs LRU on vLLM, and p99 from 26.0 s to 16.8 s. The median got worse, 112 to 171 ms. Evicting the same way block by block fragmented the prefixes and had 4.0x LRU's time-to-first-token. Liu, Yu, Yang (Harvard), arXiv, 24 Sep

Moneyview is going public at about half what its last private investors paid. At the top of its ₹32-34 price band, the Indian lending app is valued at ₹5,235 crore before new shares are issued. Its last priced private rounds, in September 2024 and March 2025, put it at about $1.2B, over ₹10,000 crore at the time, per Tracxn. This isn't a company in trouble. Its restated financials show income up 43% last fiscal year and a ₹243 crore profit. But profit grew 1%, and the IPO price is about 21 times it. It has also halved the new money it is raising, from ₹1,500 crore in its draft papers to ₹750 crore. A private round sets the price one investor agreed to. An IPO asks the whole market.

Legal tech logged 111 funding rounds this year, per Tracxn. Two companies took half the money. Harvey: $200M in March, $550M in August. Legora: $550M in March, $50M in April. Four rounds, $1.35B of the $2.73B disclosed across 96 rounds. Narrow it to AI-native legal startups and those four rounds are 86% of the dollars. The gap behind them is steep. The biggest round outside the pair, Noxtua's $115M Series C this week, is about a fifth of either leader's largest raise. That looks less like a category being funded than a two-company race being financed. For everyone else in legal tech, the pitch can't just be "AI for lawyers" anymore. It has to answer: why not Harvey or Legora?

So essentially is Anime is cartoon from Japan.

A better benchmark score is not faster code. I scripted a candidate with a fast path only when len(xs) == 4000, the benchmark's exact input. chi scored it 99.7% faster. On 900, 3300 and 9000 elements it gained nothing: -4.1%. chi's new holdout gate caught it: overfit.

Since the 1980s, the standard story for why GaAs grown on silicon fills with antiphase boundaries: single-atom steps on the Si surface flip which sublattice Ga and As land on. Hence miscut wafers, tilted to pair those steps up. A review posted this week argues the steps don't do it. What it pulls together: - DFT puts a charge-compensated GaP/Si interface at 23.4 to 27.3 meV/Ų, below abrupt interfaces (30 to 70). Half the top Si plane swaps for group-III atoms, one stable configuration everywhere. - Growth starts as nm-scale 3D islands, each a single domain, spreading across many terraces. Too small for AFM, and their fast merging looks like a continuous film in TEM, which is how they were long read as 2D growth. - At a step edge, changing the interface configuration costs far less energy than forming a boundary. So the boundaries form where independently nucleated islands meet. In their thought experiment, one island would stay a single domain across any number of steps. Miscut isn't free: it misaligns the crystal's natural cleavage planes, which complicates laser cavities. If the review is right, the thing to control is how islands nucleate and merge, not step structure. Cornet et al., arXiv, 21 Sep

A single postmortem snapshot shouldn't be able to tell you rates. For protein aggregates in brain tissue, a new model says the length histogram can. Assume large fibrils grow one monomer at a time at their ends and get cleared at a rate that doesn't depend on their length. At steady state, the number of aggregates then falls by the same factor α with every added monomer: a straight line on a log-linear histogram. The slope reads out clearance relative to growth directly, as 1/α − 1. Nucleation drops out. Making more aggregates changes how many you see, not the shape. What makes it usable: microscopes measure nanometres, not monomers, and that conversion is rough. Compare two samples by the ratio of their clearance-to-growth numbers and the conversion factor cancels to leading order, as long as fibrils are hundreds of monomers long. Departures are diagnostic too. Fragmentation bends the line downward; the authors haven't yet seen that in a human sample. Tissue that mixes cells clearing well with cells that can't keep up gives two slopes, and the struggling cells own the long tail. Cotton, Klenerman and Meisl, Cambridge (arXiv, 22 Sep)

Order-book depth in my trading system was growing about 137 GB a year, with nothing deleting it. The recorded plan: month partitions, keep 90 days. Dropping partitions would have broken something unrelated. Each option-chain row holds both the depth ladders (delete after 90 days) and the bid, ask, Greeks and session bar (keep indefinitely). Learning labels are verified against digests of snapshot identities going back 400 days, so a 90-day partition drop would have failed every older label with an error blaming tampering. The unit of deletion was a column, not a row. Retention is an UPDATE that empties the twelve ladder arrays and records when it ran. The append-only trigger allows only that: it compares to_jsonb(OLD) with to_jsonb(NEW), those thirteen columns stripped, and refuses unless the rest is identical. A column added next year is protected the day it lands.

Landed in US, booked a cab from @lyft to go to my hotel & saw a note that my driver is deaf/ hard of hearing. The app also prompted me on how to use helpful American Sign Language phrases. And as it turns out, when the cab arrived, my driver was indeed deaf. He handed over a card stating so & welcoming me. And I said thank you in sign language. Will we ever have the same level of opportunity and respect for specially enabled people in India & go beyond just offering them a quota in Government jobs. There may be thousands of things wrong with the US & troll me for it but as a country, it truly does provide equal opportunity for all, regardless of disability. India, we all need to step up.

Nvidia, AMD and Broadcom bought none of the 19 funded companies in Tracxn's semiconductor category that were acquired this year. The big cheques came from quieter incumbents. Analog Devices paid $1.5B for Empower Semiconductor and $1.35B for Alif Semiconductor, its only two deals of 2026. TE Connectivity paid $1.4B for Astrodyne TDI. Microchip closed its Hailo deal on 21 September, price undisclosed; Hailo's last round valued it at $1.2B. What they bought is power delivery, power supplies, low-power microcontrollers and edge AI chips. Not the data-center accelerators that dominate the headlines. Seven of the 19 disclosed a price, $5.73B in total. Analog Devices alone is just under half of it. For a chip startup this year, the likely buyer was not an AI giant. It was a company that sells the unglamorous parts inside everything.

My agents have a shell, so they can call the leaderboard CLI. In dogfood they did, for benchmarks. A ranked submit could burn the rate limit. chi puts a shim first on their PATH: benchmark passes, --mode leaderboard exits 3. A speed bump, not a sandbox. Auth stays on disk.

A new benchmark ran 12 generative crystal-structure models against plain template lookup. The lookup won: 68.3% top-1 on 180 structures, with EquiCSP next at 66.4%. Most structures the generators got right, template substitution got right too. Then the authors removed four whole prototype families from training and retrained the best generator. Its accuracy on those families fell 50-78%. So today's generative CSP models behave mostly like softer prototype libraries. The few structures that survived the removal are the genuinely predictive part, and that is what the paper says should be measured. Wei et al., arXiv 2609.26502, 22 Sep 2026

A T cell can respond to a handful of foreign peptides among a sea of self ones. A new model says the self peptides may be doing the amplifying. arXiv, 22 Sep: a 5x5 cluster of receptors, many weak "incorrect" ligands, one strong "correct" one. Neighbouring receptors are coupled to prefer the same bound or free state, and kinetic proofreading means a weak bond usually breaks before its receptor finishes activating. Incorrect ligands alone activate nothing. Bind one correct ligand and it becomes a nucleation seed: its neighbours now hold their weak ligands long enough to activate, and most of the cluster lights up, even as the correct ligand unbinds and rebinds elsewhere. It maps onto an Ising cluster. Decoy concentration plays the magnetic field, and the correct ligand is a local field that tips the flip. The coupling has a window: too weak and nothing spreads, too strong and the flip is too slow. The decoys are the amplifier. That fits a 2002 Nature paper finding that self-recognition raised naive T cells' sensitivity to foreign antigen.

A test suite went red on 20 September with no commit behind it. The fixture pinned one clock function and left its sibling on the real clock. Each capture reads both and stores the gap between them in a 32-bit column of milliseconds. The fixture was dated 26 August, so the gap grew by a day every day. 2^31 ms is 24.9 days. Past that, Postgres refused the insert: integer out of range. The fix pins the root clock the other one is derived from, so both sides read one clock. The write also refuses a gap that size by name now, instead of letting the driver fail mid-insert.

The same buyer took two software companies five weeks apart, each at roughly a tenth of its peak private valuation. One deal is worth nearly three times all the money ever put into that company. The other is worth less than the money put in. Bending Spoons agreed on 10 September to buy Miro for $1.36B. Miro's last priced round, January 2022, valued it at $17.5B. Total ever raised: $476M. Its Airtable deal, announced 4 August and closed 4 September, was $1.285B. Airtable's last mark was $11B in December 2021. Total ever raised: $1.353B. Miro's price is 2.9x all capital raised. Airtable's is 0.95x. The discounts off the peak are close, 92% and 88%. The difference is that Airtable needed nearly three times as much capital to reach a lower mark. How much of either sale reaches common shareholders depends on preference terms that were never public. A steep markdown and a bad outcome are not the same number. Tracxn acquisition and funding records.