Image is from the Wikipedia article on the Sudanese Civil War.

Al-Fashir, the capital of North Darfur (a little east of that deep red zone in the west of the megathread map), is the last major holdout of the Sudanese government in that state, and is currently under siege by the RSF. Losing it would be a significant blow to the SAF, though given how the conflict lines are shaping up, it seems increasingly plausible that there will be a de facto - if not de jure - partition of Sudan, unless the military situation substantially changes. This is because the RSF have been pushed out of central Sudan, while the SAF are being pushed out of Western Sudan - although, the situation is pretty complex and has been known to change rapidly before.

As has been a constant feature of the Sudan Civil War - perhaps the single worst humanitarian crisis on the planet right now when measured by numbers - the civilian situation pales in comparison to the military situation, with hundreds of thousands of children dead from famine, and tens of millions of people experiencing extreme food insecurity.

Al-Fashir has been the destination of many thousands of refugees fleeing genocide, and food and aid supplies into the town are being explicitly blocked by the RSF, resulting in scenes similar to what is happening in Gaza right now. The big difference is that fleeing from major battle zones is at least somewhat of an option, though people are often caught and robbed or enslaved or trafficked while moving to neighbouring towns and cities - and these cities are often experiencing similar conditions to places that refugees are leaving.

Last week’s thread is here.
The Imperialism Reading Group is here.

Please check out the RedAtlas!

The bulletins site is here. Currently not used.
The RSS feed is here. Also currently not used.

Israel's Genocide of Palestine

If you have evidence of Zionist crimes and atrocities that you wish to preserve, there is a thread here in which to do so.

Sources on the fighting in Palestine against the temporary Zionist entity. In general, CW for footage of battles, explosions, dead people, and so on:

UNRWA reports on Israel’s destruction and siege of Gaza and the West Bank.

English-language Palestinian Marxist-Leninist twitter account. Alt here.
English-language twitter account that collates news.
Arab-language twitter account with videos and images of fighting.
English-language (with some Arab retweets) Twitter account based in Lebanon. - Telegram is @IbnRiad.
English-language Palestinian Twitter account which reports on news from the Resistance Axis. - Telegram is @EyesOnSouth.
English-language Twitter account in the same group as the previous two. - Telegram here.

English-language PalestineResist telegram channel.
More telegram channels here for those interested.

Russia-Ukraine Conflict

Examples of Ukrainian Nazis and fascists
Examples of racism/euro-centrism during the Russia-Ukraine conflict

Sources:

Defense Politics Asia’s youtube channel and their map. Their youtube channel has substantially diminished in quality but the map is still useful.
Moon of Alabama, which tends to have interesting analysis. Avoid the comment section.
Understanding War and the Saker: reactionary sources that have occasional insights on the war.
Alexander Mercouris, who does daily videos on the conflict. While he is a reactionary and surrounds himself with likeminded people, his daily update videos are relatively brainworm-free and good if you don’t want to follow Russian telegram channels to get news. He also co-hosts The Duran, which is more explicitly conservative, racist, sexist, transphobic, anti-communist, etc when guests are invited on, but is just about tolerable when it’s just the two of them if you want a little more analysis.
Simplicius, who publishes on Substack. Like others, his political analysis should be soundly ignored, but his knowledge of weaponry and military strategy is generally quite good.
On the ground: Patrick Lancaster, an independent and very good journalist reporting in the warzone on the separatists’ side.

Unedited videos of Russian/Ukrainian press conferences and speeches.

Pro-Russian Telegram Channels:

Again, CW for anti-LGBT and racist, sexist, etc speech, as well as combat footage.

https://t.me/aleksandr_skif ~ DPR’s former Defense Minister and Colonel in the DPR’s forces. Russian language.
https://t.me/Slavyangrad ~ A few different pro-Russian people gather frequent content for this channel (~100 posts per day), some socialist, but all socially reactionary. If you can only tolerate using one Russian telegram channel, I would recommend this one.
https://t.me/s/levigodman ~ Does daily update posts.
https://t.me/patricklancasternewstoday ~ Patrick Lancaster’s telegram channel.
https://t.me/gonzowarr ~ A big Russian commentator.
https://t.me/rybar ~ One of, if not the, biggest Russian telegram channels focussing on the war out there. Actually quite balanced, maybe even pessimistic about Russia. Produces interesting and useful maps.
https://t.me/epoddubny ~ Russian language.
https://t.me/boris_rozhin ~ Russian language.
https://t.me/mod_russia_en ~ Russian Ministry of Defense. Does daily, if rather bland updates on the number of Ukrainians killed, etc. The figures appear to be approximately accurate; if you want, reduce all numbers by 25% as a ‘propaganda tax’, if you don’t believe them. Does not cover everything, for obvious reasons, and virtually never details Russian losses.
https://t.me/UkraineHumanRightsAbuses ~ Pro-Russian, documents abuses that Ukraine commits.

Pro-Ukraine Telegram Channels:

Almost every Western media outlet.
https://discord.gg/projectowl ~ Pro-Ukrainian OSINT Discord.
https://t.me/ice_inii ~ Alleged Ukrainian account with a rather cynical take on the entire thing.

  • Sebrof [he/him, comrade/them]@hexbear.netEnglish
    8·
    3 days ago

    Some quotes I’ve pulled out from that first article you sent, as well as another article cited that goes into some details on the AI bubble.

    Google, Amazon, and Meta are soaring past $2 trillion, and now Apple is well past $3 trillion. Much of this expansion of value has occurred in just the last two years, on the back of the AI boom.

    Microsoft and Nvidia are benefitting from bona fide historic levels of investment… Paul Kedrosky in his most recent column in the Wall Street Journal:

    spending on AI infrastructure has already exceeded spending on telecom and internet infrastructure from the dot-com boom—and it’s still growing… one explanation for the U.S. economy’s ongoing strength, despite tariffs, is that spending on IT infrastructure is so big that it’s acting as a sort of private-sector stimulus program

    Capex spending for AI contributed more to growth in the U.S. economy in the past two quarters than all of consumer spending, …

    Over the last six months, capital expenditures on AI—counting just information processing equipment and software, by the way—added more to the growth of the US economy than all consumer spending combined.

    There’s also a longer article mentioned, and here are some quotes pulled from it, but I didn’t get a chance to read through it all. From The Hater’s Guide To The AI Bubble

    The Magnificent 7 stocks — NVIDIA, Microsoft, Alphabet (Google), Apple, Meta, Tesla and Amazon — make up around 35% of the value of the US stock market, and of that, NVIDIA’s market value makes up about 19% of the Magnificent 7.

    Microsoft (18.9%), Amazon (7.5%), Meta (9.3%), Alphabet (5.6%), and Tesla (0.9%) alone make up 42.4% of NVIDIA’s revenue. The breakdown makes things worse. Meta spends 25% — and Microsoft an alarming 47% — of its capital expenditures on NVIDIA chips

    In simpler terms, 35% of the US stock market is held up by five or six companies buying GPUs.

    … by the end of 2025, Meta, Amazon, Microsoft, Google and Tesla will have spent over $560 billion in capital expenditures on AI in the last two years, all to make around $35 billion.

    The Information reports that Microsoft made $4.7 billion in “AI revenue” in 2024, of which OpenAI accounted for $2 billion, meaning that for the $135.7 billion that Microsoft has spent in the last two years on AI infrastructure, it has made $17.7 billion, of which OpenAI accounted for $12.7 billion.

    Things do not improve elsewhere. … Amazon, which plans to spend $105 billion in capital expenditures this year, will make $5 billion on AI in 2025, rising, and I quote, “as much as 80%,” suggesting that Amazon may have made a measly $2.77 billion in 2024 on AI in a year when it spent $83 billion in capital expenditures.

    Some people compare Large Language Models and their associated services to Amazon Web Services, or services like Microsoft Azure or Google Cloud, and they are wrong to do so

    These services are… selling infrastructure. You aren’t just paying for the compute, but the ability to access storage and deliver services with low latency

    …ultimately cloud services are about Amazon, Microsoft and Google running your infrastructure for you. Large Language Models and their associated services are completely different, despite these companies attempting to prove otherwise, and it starts with a very simple problem: why did any of these companies build these giant data centers and fill them full of GPUs?

    Amazon Web Services was created out of necessity — Amazon’s infrastructure needs were so great that it effectively had to build both the software and hardware necessary to deliver a store that sold theoretically everything to theoretically anywhere, handling both the traffic from customers, delivering the software that runs Amazon.com quickly and reliably, and, well, making sure things ran in a stable way. It didn’t need to come up with a reason for people to run web application.

    Yet after that, generative AI feels more like a feature of cloud infrastructure rather than infrastructure itself. AWS and similar megaclouds are versatile, flexible and multifaceted. Generative AI does what generative AI does, and that’s about it. You can run lots of different things on AWS. What are the different things you can run using Large Language Models? What are the different use cases, and, indeed, user requirements that make this the supposed “next big thing”?

    We’re three years in, and generative AI’s highest-grossing companies — outside OpenAI ($10 billion annualized as of early June) and Anthropic ($4 billion annualized as of July), and both lose billions a year after revenue — have three major problems:

    • Businesses powered by generative AI do not seem to be popular.
    • Those businesses that are remotely popular are deeply unprofitable…
    • …and even the less-popular generative AI-powered businesses are deeply unprofitable.

    Cursor’s $500 Million “Annualized Revenue” Was Earned With A Product It No Longer Offers…

    Cursor raised $900 million and very likely had to hand large amounts of that money over to OpenAI and Anthropic to keep doing business with them, and then immediately changed its terms of service to make them worse.

    Cursor is the largest and most-successful generative AI company, and these aggressive and desperate changes to its product suggest

    • A) that its product is deeply unprofitable and
    • B) that its current growth was a result of offering a product that was not the one it would sell in the long term

    Outside of OpenAI, Anthropic and Anysphere (which makes AI coding app Cursor), there are no Large Language Model companies that make more than $500 million in annualized revenue… [and] there are only twelve generative AI-powered companies making $100 million annualized.

    Generative AI Has No Business Model If It Can’t Do Software As A Service

    … in the world of Software-as-Service or enterprise software, [the revenues of AI companies are] chump change. Hubspot had revenues of $2.63 billion in its 2024 financial year.

    Netflix makes about $39 billion a year in subscription revenue, and Spotify about $18 billion.

    Compare to OpenAI’s $10 billion annualized.

    … OpenAI’s 15.5 million subscribers suggest that it can’t rely on them for the kind of growth that would actually make the company worth $300 billion (or more).

    Really, Where Are The Consumer AI Startups I’m serious. Perplexity? Perplexity only has $150 million in annualized revenue! It spent 167% of its revenue in 2024 ($57m, its revenue was $34m) on compute services from Anthropic, OpenAI, and Amazon! It lost $68 million!

    And worse still, it has no path to profitability, and it’s not even anything new! It’s a search engine!

    And don’t talk to me about “AI browsers,” I’m sorry, it’s not a business model. How are people going to make revenue on this, hm? What do these products actually do?

    … it doesn’t seem like you can really build a consumer AI startup that makes anything approaching a real company. Other than ChatGPT, I guess?

    The Generative AI Software As A Service Market Is Small, With Little Room For Growth And No Profits To Be Seen

    But the worst sign is that nobody is saying the monthly figures, mostly because the monthly figures kinda suck! $100 million of annualized revenue is $8.33 million a month. To give you some scale, Amazon Web Services hit $189 million ($15.75 million a month) in revenue in 2008, two years after founding, and while it took until 2015 to hit profitability, it actually hit break-even in 2009, though it invested cash in growth for a few years after.

    Right now, not a single generative AI software company is profitable, and none of them are showing the signs of the kind of hypergrowth that previous “big” software companies had.

    If you look at what generative AI companies do…, it’s probably doing one of the following things:

    • A chatbot, either one you ask questions or “talk to”
    • This includes customer service bots-
    • Searching, summarizing or comparing documents, with increasing amounts of complexity of documents or quantity of documents to be compared
    • This includes being able to “ask questions” of documents
    • Web Search
    • “Deep Research” — meaning long-form web search that generates a document
    • Generating text, images, voice, or in some rare cases video
    • Using generative AI to to write, edit or “maintain” code
    • Transcription
    • Translation
    • Photo and video editing

    Every single generative AI company that isn’t OpenAI or Anthropic does one or a few of these things, and I mean every one of them, and it’s because every single generative AI company uses Large Language Models, which have inherent limits on what they can do. LLMs can generate, they can search, they can edit (kind of!), they can transcribe (sometimes accurately!) and they can translate (often less accurately).

    As a result, it’s very, very difficult for a company to build something unique

    … when your services are dependent on a Large Language Model, are dependent on the model developer, who, in the case of OpenAI and Anthropic, could simply clone your startup, because the only valuable intellectual property is theirs.

    Generative AI Is Simply Too Expensive To Build A Sustainable Business On Top Of It

    Damn, if only there was some sort of philosopher or political economist who had written about something like this. Oh well.

    This is more, but this is already getting a bit long.