lol. lmao, even.

EUSP (European Search Perspective) is our joint venture with Qwant to build a European search index. We started serving results to users in France last year, and now we’re excited to go live in Germany too

A big leap forward.

Die Wörter sind von hier

https://ulm5.info/en/

The Ulm 5 – who include two UK citizens, one Irish, one Spanish and one German – have been accused of breaking into the site of the German subsidiary of Israeli arms manufacturer Elbit Systems, in Ulm, Southwest Germany, on 8th September 2025, and of damaging property.

I have a very pragmatic view on music: all I care about is whether it sounds good or not. That's it. That's literally it. And from that standpoint the advent of AI music has been a major net positive for me.

You can choose to ignore that and come tell me about the ethics of using AI or how you care about the story behind the song and so on and that's all fine but just note that you're no longer addressing what I'm actually saying here.

I'm also not claiming it's great - only that it's good. I've yet to discover an AI song that I go back to like I do with many human-made songs but if I want to put on a playlist playing in the background then one consisting of entirely AI-made music reliably provides me well above average track after another whereas with organic music I need to sift through a ton of absolute crap to stumble upon the occasional good track that still rarely exceeds what AI is able to output. I can go on YouTube and put on a 2 hour playlist of Jazz House or similar and I don't get the urge to skip a single track.

Currently I feel like where AI still trips is lyrics - they still are only plausible sounding nonsense once you actually start paying attention to it but especially for instrumental music it has far exceeded the level of a good average human artist.

Few examples of what I'm refering to: with vocals and without.

Defense Secretary Gibo Teodoro’s remark that profits from the proposed Pax Silica AI hub should flow to the AFP because the project falls under the Bases Conversion Development Authority (BCDA) is both revealing and deeply insulting to the Filipino people. Why should the Filipino people pay for the guns pointed at their own heads?

By declaring that profits should flow to the AFP, Teodoro has confirmed what many have already known – that Pax Silica is not meant to generate jobs for Filipinos as Marcos Jr. histrionically promoted in his last SONA, it is instead a war chest for militarization.

His remarks are made worse by the AFP’s bloody record of bombing and militarization of communities in repeated violations of international humanitarian law. Following the recent clash in Naujan, Oriental Mindoro, the 203rd IB publicly posted photographs of supposed slain fighters on social media as their trophies of war – an act that violates the principles of dignity and humane treatment of the dead embodied in IHL. In the aftermath of the encounter, military checkpoints were also established across Naujan, further tightening armed military presence in civilian communities.

The brazenness of Teodoro and Marcos Jr’s bootlicking to their US master is not only reflected in their efforts to siphon resources towards the AFP, but also in the aggressive expansion of war games and military exercises in recent months. The use of live ammunition, missile systems, and other weapons of war in these exercises places civilians directly in harm’s way. As the Marcos administration pours resources to the AFP, it is simultaneously transforming the Philippines into a staging ground for US war preparations, placing the Filipino people at greater risk.

We urge the Filipino people to reject any proposal that funnels the wealth generated from our labor, land, and resources into the hands of the fascist AFP and its US imperialist masters.

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Artificial Analysis @ArtificialAnlys · 5m DeepSeek V4 Flash 0731 scores 50 on the Artificial Analysis Intelligence Index, a 10-point jump over DeepSeek V4 Flash (released April 2026) that puts it 6 points ahead of DeepSeek V4 Pro. It shares identical architecture and pricing with the earlier DeepSeek V4 Flash, and lands on our Pareto frontier for Intelligence vs Cost per Task

@deepseek_ai ’s DeepSeek V4 Flash 0731 is one Intelligence Index point behind GPT-5.6 Luna (max, 51). Even after OpenAI’s 80% price cut on GPT-5.6 Luna today, DeepSeek V4 Flash 0731’s Cost per Task on DeepSeek’s first-party API comes in at ~60% lower than GPT-5.6 Luna (max), a model with comparable intelligence. A key driver of this is DeepSeek’s ~98% cache hit discount on its first-party API, a significantly more aggressive discount than the 90% cache hit discount offered by most of the industry

The new model is a significant step up from the previous generation, DeepSeek V4 Flash (40), and places the model within 1 point of GLM-5.2 (max, 51). It remains 7 points behind the open weights frontier set by Kimi K3 (max, 57). For additional context, this places the model in line with recently released Gemini 3.6 Flash (50) and 1 point behind Muse Spark 1.1 (xhigh, 51). DeepSeek is expected to release the model’s full weights in the coming weeks

DeepSeek V4 Flash 0731 retains a 1M token context window, and its size remains unchanged from DeepSeek V4 Flash at 284B total parameters and 13B active at inference time

Key results:

➤ Improvements in agentic performance: DeepSeek V4 Flash 0731 achieves an Elo rating of 1559 on GDPval-AA v2, our evaluation focused on agentic real-world work tasks, up from 1189 for the previous DeepSeek V4 Flash. Once weights are released this will be the second highest open weights score, behind Kimi K3 (max, 1687) and ahead of GLM-5.2 (max, 1510). Terminal-Bench 2.1 rises 17 points to 79% and τ³-Bench Banking 8 points to 31%

➤ Token usage falls 12% against the predecessor: DeepSeek V4 Flash 0731 used ~206M output tokens to run the Intelligence Index, against ~234M for the previous DeepSeek V4 Flash. The new variant is more token efficient, achieving a higher Intelligence Index with a lower number of total output tokens

➤ DeepSeek V4 Flash 0731 improves over its predecessor on every evaluation in the Intelligence Index: Alongside the agentic gains, CritPt gains 9 points to 17%, SciCode 5 points to 50%, Humanity's Last Exam 5 points to 37%, AA-LCR 3 points to 66% and GPQA Diamond 1 point to 91%

➤ AA-Omniscience improvements are driven by fewer hallucinations, rather than higher accuracy: DeepSeek V4 Flash 0731 achieves an AA-Omniscience Index of -16, a +7 improvement from its predecessor. This improvement is purely driven by a reduced hallucination rate, with overall accuracy (percentage correct) unchanged. Its AA-Omniscience Hallucination Rate is 84%, a 12 point decrease from its predecessor, and comparable to models such as GPT-5.6 Terra (max, 85%) and Mistral Medium 3.5 (82%)

Additional model details:

➤ Context window: 1M tokens (equivalent to DeepSeek V4 Flash)

➤ Size: 284B total parameters (13B active)

➤ Input modalities: Text input and output only

➤ Accessibility: Available through DeepSeek’s first-party API

➤ Pricing: $0.14/$0.28 per 1M input/output tokens, unchanged from DeepSeek V4 Flash. Cache hit price of $0.0028 per 1M tokens, a 98% discount

July 30, 2026