Wiki Lint Report — 2026-09-20
Automated lint: 14 errors, 54840 warnings, 3 info
Knowledge catalogue
Automated lint: 14 errors, 54840 warnings, 3 info
arXiv:2609.17632v1 Announce Type: new Abstract: Large language model (LLM) trading agents can combine market data, news, and executable analysis, but their behavior is often controlled by static hand-
arXiv:2609.19096v1 Announce Type: cross Abstract: Artificial intelligence (AI) is increasingly integrated into healthcare systems worldwide, yet its successful clinical adoption depends critically on
arXiv:2609.16069v1 Announce Type: cross Abstract: Synthetic tabular data can match real data distributions while still violating the semantic constraints that govern valid tabular rows. This reveals a
Learn how to automate end-to-end PII detection and redaction from scanned documents at scale using Amazon Bedrock Data Automation with a custom blueprint, AWS Step Functions, and AWS Lambda. A custom
Automated lint: 12 errors, 54839 warnings, 3 info
Financial Times: Sources: Anthropic told investors it will be profitable for a second straight quarter, with 80%+ gross margins before partner revenue sharing and training costs — Claude maker seeks t
Hey y'all! We've released a new model in our lineup: GigaChat-3.5 Reasoning. It's a 432B-A28B MoE with Gated DeltaNet for long-context efficiency. We trained domain experts (code, math, general, etc.)
Q2D-Web uses agent citations, production web rankings, and a combined set expanded with LLM judgments. These three relevance sets reduce false negatives and reliance on a single labeling pipeline, whi
Led by @Samsung, co-led by @eqt's Scaleup Europe Fund and @PSG_equity, with continued backing from @ASMLcompany, @nvidia, @BNPParibas CIB and others. This fuels our infrastructure and product capabili
The missing control is visible in sudoingX’s Ling-3.0-flash benchmark graphics. The earlier table leaves Ling’s no-speculation baseline as “not measured.” The later code/prose graphic fills it in: abo
Learn how to customize an Amazon Bedrock knowledge base for large, complex documents by combining the high-accuracy text extraction of Amazon Textract with the generative AI of Amazon Bedrock. This po
It sounds like the shift back toward open weight models that I noticed among the startups in the summer batch is a genuine trend. 🦙 @ollama is used by 9 million developers and 85% of the Fortune 500,
Robbie Whelan / Wall Street Journal: Sources: US negotiators used the promise of access to Nvidia's chips for an Armenian data center to broker a preliminary Armenia-Azerbaijan peace deal last year —
arXiv:2609.03218v1 Announce Type: new Abstract: Large Language Models (LLMs) increasingly use user context such as memory, profiles, and role prompts to personalize their responses. This personalizati
arXiv:2609.00818v1 Announce Type: new Abstract: We argue that financial report generation should operate at the analytical rather than structural level, composing content from data-derived insights ra
arXiv:2608.24621v2 Announce Type: replace Abstract: Can language models be trusted in safety- critical operations? In such settings, strong per- formance on semantic metrics does not guaran- tee opera
Bloomberg: Nvidia plans to invest 3.5B into MediaTek through convertible bonds; MediaTek forecasts AI chip revenue of about 2B this year — Nvidia Corp. is investing $3.5 billion into MediaTek Inc., de
arXiv:2608.26119v1 Announce Type: new Abstract: Whether large language models can be prompted to generate rhetorical fallacies on demand, and whether current safety post-training constrains this behav
Asa Fitch / Wall Street Journal: Nvidia says its commitments to component suppliers for its AI chips and systems hit 279B in Q2, up from 119B in Q1, 95.2B in Q4 2025, and 50.3B in Q3 2025 — The AI chi
Protecting capital in today's markets requires immense speed and precision. A financial analyst preparing a deal memo works across licensed market data, internal models, and confidential client files.
Perplexity has low tens of millions in revenue a month, and I’m not even talking about how much they lose. Nvidia had to step in to boost their valuation and give them first aid, either through cloud
Yoolim Lee / Bloomberg: Sources: Nvidia is in early talks with South Korean AI chip maker Rebellions for a potential deal, including a partnership, an investment, or an acquisition — Nvidia Corp. is i
Healthcare, retail, and life sciences teams store large volumes of operational data in Snowflake, but turning it into predictions is hard. In Part 1 of this series, you set up your AWS account and Sno
Since announcing Google Antigravity in Gemini Enterprise Agent Platform at I/O in May, we’ve heard helpful feedback from our customers. Your developers want easy access to coding agents across surface
Bloomberg: Filing: Nvidia agrees to spend up to 105B to support SB Energy's new data center campus in Ohio set to be leased by OpenAI; Nvidia invests 1.5B in SB Energy — Nvidia Corp. has agreed to spe
Anissa Gardizy / Wall Street Journal: OpenAI signs a 20-year, 10GW data center deal in Ohio with SoftBank's SB Energy; Nvidia agrees to backstop a portion of the value of the completed data center — A
Guess who gets f_cked in the end? “.. Nvidia gets paid upfront, the borrowers and their lenders carry the default risk, and because private credit is ultimately funded by ordinary savers through instr
Ideas are the new bottleneck @akshaynathan_, Core Product Engineering, @OpenAI, interviewed by @swyx and @Vibhu (@LatentSpacepod) Summary: Akshay Nathan runs the productivity pillar at OpenAI, the tea
The Information: Sources: Nvidia in talks to invest up to 3B in SoftBank-backed data center developer SB Energy that aims to IPO soon and is behind a huge OpenAI campus in Ohio — Nvidia is in talks to
arXiv:2608.13484v1 Announce Type: cross Abstract: When asked about entities outside their knowledge boundary, LLMs routinely fabricate plausible-sounding details rather than backing off to safer, more
This is so much bigger than one company, and orders of magnitude more dangerous to the economy and investors than Enron. Nvidia’s AI push has echoes of Enron, says Big Short investor https://www.teleg
arXiv:2503.05061v3 Announce Type: replace Abstract: Reliable evaluation of large language models (LLMs) is critical as their deployment rapidly expands, particularly in high-stakes domains such as bus
Julian Hast / Bloomberg: OpenAI is hiring a power-trading lead to manage commodity hedging across its expanding data center power portfolio, as tech companies seek reliable electricity — OpenAI is hir
arXiv:2608.07493v1 Announce Type: cross Abstract: Current AI disclaimers often fail to function as intended due to warning habituation and a transparency paradox. As AI-generated information becomes p
Vlad Savov / Bloomberg: Meta says Muse Glimmer has 30B parameters and is “small enough” to need only one GPU; Meta plans a $1B fund to invest in US communities near its data centers — Meta Platforms I
arXiv:2607.23120v1 Announce Type: cross Abstract: Stock recommendation systems face the dual challenge of adapting to rapidly changing market conditions while maintaining low-latency predictions for e
arXiv:2607.24589v1 Announce Type: new Abstract: The development of the Innovative Ecosystem (IE) presents a new paradigm for economic integration, collaborative advancement, and shared achievements. T
🦔The cost of insuring Big Tech debt against default just hit record highs. Credit default swaps are insurance policies investors buy when they think a company might not pay back what it borrowed. When
Reuters: Nvidia and SK Group unveil a 500B+ AI initiative that includes an SK Hynix partnership to secure next-gen memory supply for Nvidia and joint development of HBM — Nvidia (NVDA.O) and South Kor
Open models matter. Ollama works hard with the model creators, hardware partners, and most importantly developers building software leveraging various open models for their own use cases. For my first
.@satyanadella's Reverse Information Paradox is real. What @satyanadella's calling for already exists: open models. Over 9M+ developers have used @ollama to access open models and keep their competiti
Artificial intelligence training data company Mercor.io Corp. announced today that it has acquired Deeptune Inc., a startup that builds simulated software environments used to train AI agents. Financi
arXiv:2412.10860v2 Announce Type: replace-cross Abstract: Quantum Support Vector Machine is a kernel-based approach to classification problems. We study the applicability of quantum kernels to financi
arXiv:2606.21013v1 Announce Type: cross Abstract: Forecasting future events is a critical challenge for large language model (LLM) agents, spanning domains from elections and monetary policy to financ
arXiv:2606.21875v1 Announce Type: cross Abstract: Modern data analysis usually gives a prediction without showing whether the evidence behind it is clear, conflicting, or stable. Two cases can have th
Meet Kimi Work - a local AI agent on your desktop that does the work for you. 🔹Native agent swarm: Up to 300 AI agents running in parallel on your local machine. 🔹Browser use: Paired with WebBridge ex
We wrapped a live session on M3 yesterday with the @togethercompute team & our researchers @zpysky1125 and @HaohaiSun A few highlights 🧵 1. MSA (MiniMax Sparse Attention) is the star ⭐️. Unlike CSA/HC
arXiv:2605.30907v1 Announce Type: cross Abstract: We present BlueFin, a benchmark that tasks large language model (LLM) agents with synthesis, manipulation, and comprehension tasks over spreadsheet wo
Many organizations’ single source of truth is data that resides in BigQuery, Google’s governed, secure and petabyte-scale data platform. However, the 'last mile' of ad-hoc analysis, modeling, and repo
arXiv:2502.10205v3 Announce Type: replace Abstract: Representation learning produces models in different domains, such as store purchases, client transactions, and general people's behavior. However,
arXiv:2605.23071v1 Announce Type: new Abstract: Large language models (LLMs) increasingly rely on long-context processing, but expanding context windows introduces substantial computational and financ
arXiv:2503.22693v2 Announce Type: replace-cross Abstract: The rapid advancements in Large Language Models (LLMs) have unlocked transformative possibilities in natural language processing, particularly
arXiv:2605.18824v1 Announce Type: cross Abstract: Evaluation of foundation models often rely on aggregate scores from benchmarks that lack comprehensive coverage and metadata for a fine-grained evalua
arXiv:2605.16613v1 Announce Type: new Abstract: We introduce a novel approach to emotion modeling that shifts the focus from identification to evaluation, addressing the limitations of discrete classi
arXiv:2503.20981v2 Announce Type: replace-cross Abstract: Investigating the public experience of urgent care facilities is essential for promoting community healthcare development. Traditional survey
arXiv:2605.13936v1 Announce Type: cross Abstract: The recent success of large language models (LLMs) has been largely driven by vast public datasets. However, the next frontier for LLM development lie
Executive Summary Since our February 2026 report on AI-related threat activity, Google Threat Intelligence Group (GTIG) has continued to track a maturing transition from nascent AI-enabled operations
arXiv:2605.05144v1 Announce Type: new Abstract: This paper reflects on a AI research project carried out by a team of high-school and early-undergraduate students under the mentorship of graduate rese
arXiv:2604.25224v2 Announce Type: replace Abstract: LLM-based financial agents increasingly produce investment rationales before the outcomes needed to evaluate them are observable. This creates a del