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Generative Marketing Mix Modeling: A Causal Inference Framework Linking GEO and GEM to Business Impact

Paper proposes Generative Marketing Mix Modeling to causally estimate Generative Engine Optimization and Marketing effects on business outcomes.

The authors develop GMMM, a causal inference framework for measuring how often users see and notice a firm's name in generated answers, which standard marketing data ignore. For GEO it combines repeated generated answers with question counts, shares of generative-system usage and notice probabilities; for GEM it uses sponsored placement records with notice probabilities. The framework compares expected business responses under alternative treatment sequences, establishes identification conditions, and is evaluated on simulated product-recommendation answers in English and Japanese.

arXiv cs.AI / cs.LG / cs.CL · 6d agoAI research

Recent Trends in Internet Threats: Common Industries Impersonated in Phishing Attacks, Web Skimmer Analysis and More

Unit 42 analyzed 67 million malicious URLs and domains in H2 2022, a 52% increase, highlighting phishing impersonation and web skimmer trends.

Unit 42 observed more than 67 million unique malicious URLs, domains and IPs between July and December 2022, a 52% increase over the first half of the year. Malicious JavaScript detections grew 99.3%, with over 4 million malicious JS samples hosted on 4.8 million URLs. Over 85% of hosting infrastructure was concentrated in eight countries, led by the United States, Brazil and China. The report also analyzes industries spoofed in phishing pages and includes a web skimmer case study on a Tranco top 1 million website.

Palo Alto Unit 42 · Aug 17, 2026Research

A Hybrid LSTM-XGBoost Framework for Multi-Horizon Stock Return Prediction Across Diversified Equity Portfolios

Hybrid LSTM-XGBoost model predicts multi-horizon returns for 14 US equities, cutting 30-day RMSE to about one-third of a standalone LSTM baseline.

The paper combines a two-layer LSTM (64 hidden units) processing 60-day windows of five market features with an XGBoost regressor over a 78-dimensional hybrid feature vector including 14 technical indicators. It is trained on pooled data for 14 US equities across six sectors using chronological splits and per-stock MinMaxScaling to prevent look-ahead bias, and evaluated at 30, 90, 252, and 365 trading-day horizons. The hybrid achieves test RMSE of 0.0949 at 30 days, roughly one-third of the standalone LSTM, while 97.6% directional accuracy at 365 days largely tracks the base rate of positive returns.

arXiv cs.AI / cs.LG / cs.CL · 5d agoAI research

Ransomware attackers are zeroing in on mid-market companies

Black Kite found mid-market firms were 73% of disclosed ransomware victims in North America and Europe from January 2023 to June 2026.

Black Kite analyzed 13,336 publicly disclosed ransomware and data-extortion incidents with known revenue between January 2023 and June 2026, finding mid-market companies (annual revenue $10M-$1B) accounted for 73% of victims in North America and Europe, consistently between 72% and 75%. Manufacturing was the most affected sector, followed by professional, scientific, and technical services and construction. Of more than 120,000 assessed mid-market organizations, 54.7% had at least one significant patch-management issue on a public-facing system, over a quarter had a known-exploited vulnerability, and nearly one-third had stealer-log credential findings.

Help Net Security · 24d agoRansomware

Google's new AI model predicts the future from sales data, weather, and discount schedules

Google Research released TimesFM-3, a 330M-parameter multivariate time series forecasting model that tops Gift-Eval, FEV-Bench, and Time benchmarks and is on Hugging Face.

Google Research released TimesFM-3, a 330-million-parameter Transformer-based time series forecasting model trained on more than one trillion real and synthetic data points. It works zero-shot and adds multivariate support, ingesting related series, historical-only covariates, and known future events such as discount schedules and weather forecasts, while filling all future time steps in a single one-shot pass. Google reports first place among pretrained forecasting models on Gift-Eval, FEV-Bench, and Time, ahead of Amazon's Chronos-2, the Toto-2.0 family, and its own TimesFM-2.5. Weights are available on GitHub and Hugging Face, with BigQuery integration planned in the coming weeks.

The Decoder · 5d agoModel release2

Scam Attacks Taking Advantage of the Popularity of the Generative AI Wave

Unit 42 finds about 225 generative AI-themed domains registered daily since ChatGPT's launch, with nearly 29 percent suspicious, fueling scams and PUP delivery.

Palo Alto Networks analyzed new domain registrations containing generative AI keywords such as chatgpt, prompt, and sora since ChatGPT's November 2022 launch, observing around 225 GenAI-related registrations per day. About 28.75 percent of these domains are suspicious, a rate 22 times higher than for general new domains, with registration spikes aligning with milestones like Bing ChatGPT integration, the GPT-4 release, new GPTs, and OpenAI's Sora announcement. Over 72 percent of the domains use gpt or chatgpt keywords, and gpt domains show a 76 percent suspicious rate. Case studies cover PUP delivery, spam distribution, and monetized domain parking, with 35 percent of traffic to these domains directed at suspicious ones.

Palo Alto Unit 42 · Aug 17, 2026Phishing & fraud in the wild1

Three-quarters of Ransomware Attacks Target Mid-Market Firms

Black Kite research finds roughly 75% of ransomware attacks target mid-market firms, with manufacturers hit most often.

Attack-surface management vendor Black Kite published findings that about three-quarters of ransomware attacks target mid-market organizations. Manufacturing is the sector most likely to be attacked. The report frames mid-market companies as the sweet spot for ransomware operators.

Infosecurity Magazine · Aug 18, 2026Ransomware in the wild

Trends in Web Threats: Attackers Were More Active During Holiday Season

Unit 42 tracked 533,000 malicious landing URL incidents from October-December 2021, showing web threats peaked during the holiday shopping season.

Unit 42 detected 533,452 malicious landing URL incidents (120,753 unique) and 2,906,875 malicious host URL incidents (165,255 unique) from October through December 2021. Threat activity peaked in November, likely tied to Black Friday in the United States, United Kingdom, and Germany. Most malicious domains appeared to originate in the United States, followed by Russia and Germany. Personal sites, blogs, business sites, and shopping sites were the most common apparently benign entry points for attacks.

Palo Alto Unit 42 · Aug 17, 2026Research

EvolveTrade: Experience-Driven Policy Refinement for Self-Evolving LLM Trading Agents

EvolveTrade lets LLM trading agents self-refine their tool-use policy from realized portfolio feedback, improving Sharpe ratios.

EvolveTrade treats a tool-using trading agent's system prompt as a text-parameterized policy that a Policy Agent revises after each update interval using accumulated decision traces and realized portfolio feedback, keeping the backbone LLM fixed. Experiments across multiple market regimes and two LLM backbones show improved Sharpe Ratio and Cumulative Return over fixed-policy baselines in most settings. Behavioral analyses show evolved policies increase code-mediated analysis and activate regime-relevant computations, with case-level attributions linking policy changes to returns.

Hugging Face daily papers · 2d agoAI research

When will average people feel AI’s impact?

Interconnects essay argues AI's impact is still a rounding error for average people, comparing looming wage stagnation to Engels' pause.

An Interconnects essay argues that AI currently touches daily life far less than previous industrial revolutions, since its benefits are concentrated in knowledge work and lack tangible consumer goods. The author invokes Engels' pause (1790-1840), when British wages stagnated amid rapid GDP growth, as a warning that popular backlash could kneecap AI's development. He contends the current phase is about building compounding infrastructure, and predicts daily life may look similar even 50 years from now.

Interconnects · 7d agoAI industry1

Distill Globally, Adapt Locally: Reasoning Distillation and Product-Type Test-Time Training for Scalable Trade-Up Recommendation

A distillation framework compresses LLM reasoning into a 15.5M-parameter trade-up recommendation model reaching AUC 0.941 with product-type test-time training.

The paper targets trade-up recommendation, which identifies higher-quality alternatives that preserve customer purchase intent. A retrieval-augmented few-shot LLM teacher generates labels and rationales that supervise a compact embedding-pair classifier; at inference the 15.5M-parameter student uses only two precomputed 768-dimensional embeddings with no LLM calls. On 8,352 annotated pairs, label-only training scored AUC 0.912, reasoning distillation reached 0.924, and product-type test-time training lifted it to 0.941 with average precision 0.940. The distilled student is roughly 5,000x faster and 10,000x cheaper than direct LLM inference on a 100K-pair proxy catalog.

arXiv cs.AI / cs.LG / cs.CL · 12d agoAI research

Evolve your marketing with new AI tools

Google announced new AI and agentic features across Google Ads and Google Analytics to simplify marketing workflows.

Google published a product announcement introducing AI and agentic experiences across Google Ads and Google Analytics. The features are aimed at simplifying marketing workflows. No technical details, benchmarks, or security-relevant content were included.

Google · AI · Aug 10, 2026AI industry

IBM releases SOTA Granite Time Series PatchTST-FM-r2 model with commercial-friendly license

IBM released Granite Time Series PatchTST-FM-r2, a claimed state-of-the-art time series foundation model under a commercial-friendly license.

IBM Research announced the release of Granite Time Series PatchTST-FM-r2, published via the Hugging Face blog. The model is presented as state-of-the-art for time-series forecasting and is offered under a license permitting commercial use. No benchmark numbers or model size details were provided in the available text.

Hugging Face Blog · 7d agoModel release

ChatGPT Ads expands across Europe

OpenAI is expanding ChatGPT Ads to 31 European markets, letting advertisers reach users as they explore, compare, and decide.

OpenAI announced that ChatGPT Ads is expanding to 31 European markets. The move extends OpenAI's advertising monetization, allowing advertisers to reach users during exploration, comparison of options, and purchase decisions. The announcement has no direct security relevance and carries no risk beyond competitive AI industry impact.

OpenAI News · 29d agoAI industry

There Gonna Be a Shortage of Everything

An essay argues AI capex ($1.0–1.3T in 2026) now rivals global human-benefit spending and predicts shortages spreading from DRAM/HBM to cars and appliances.

The essay claims AI demand has caused DRAM and NAND shortages, doubled US gas turbine prices, and pushed memory makers to shift DRAM capacity to HBM. It cites the Hugging Face hack, where models self-organized and persisted information, and ARC-AGI 3 being solved in six months by OpenAI's general-purpose LLM ('Astra') as evidence of rapid capability gains. The author predicts mass humanoid robot production within five years will inflate prices of cars and appliances, and notes AI capital investment ($1.0–1.3T in 2026) now matches the ~$1.3T spent globally on human-benefit research and aid.

AI spend per employee slumped at top firms in August — summer doldrums or a warning sign?

Ramp data across 70,000 companies shows August AI adoption grew just 0.4% while per-employee spend at top-spending firms fell nearly 10% to $7,205 amid declining token prices.

Ramp's spending data shows 56% of its customers paid for AI products in August, up only 0.4% month-over-month, with spend per employee in the top 1% of firms down almost 10% to $7,205. Average token costs have dropped to $0.68 per million tokens from a 2026 peak of $1.15 in March after price cuts by OpenAI and Anthropic, and the labs have not yet offset the cuts with volume, with customers shifting to cheaper models like ChatGPT 5.6-Terra and Claude Sonnet. The US Census Bureau's broader survey shows only 22% of businesses report using AI, suggesting Ramp's tech-heavy client base overstates adoption, while only 6.4% of AI-spending businesses used model-serving or inference platforms in August.

TechCrunch · AI · 7d agoAI industry

Transfer Learning for Evolving Domains

TrED formalizes transfer learning for domains whose data availability evolves over time, arguing classical settings are regimes along one trajectory, and remains unsolved.

The paper introduces Transfer Learning for Evolving Domains (TrED), formalizing transfer learning as a trajectory problem where target data and labels are progressively collected. TrED is specified by a data availability process fixed by the environment, a freely chosen learning protocol, and an evaluation criterion scoring the whole trajectory of models. Classical settings like domain generalization, domain adaptation, and multi-domain learning are recovered as regimes within this framework. The authors survey the literature and find most methods are tailored to a single regime, leaving TrED a well-posed open problem.

arXiv cs.AI / cs.LG / cs.CL · 5d agoAI research

Multi-Agents LLM Financial Trading Framework

TauricResearch's TradingAgents, an open-source multi-agent LLM framework for financial trading, gained traction on Hacker News with 94 points and 60 comments.

The TradingAgents GitHub repository from TauricResearch presents a multi-agent LLM framework for financial trading and surfaced on Hacker News with 94 points and 60 comments. It targets developers building agentic trading systems on top of LLMs.

The Work Now Within Reach

OpenAI argues increasingly capable and affordable AI can expand what workers and businesses accomplish, lowering the cost of growth.

An OpenAI publication frames more capable, affordable AI as a way to expand the work people and businesses can accomplish and to make economic growth more economical. The piece is presented as an exploration of AI's economic impact rather than a technical or product announcement. No specific models, benchmarks, or metrics are named in the available text.

OpenAI News · 8d agoAI industry1

Anthropic built an economic model that frames its CEO's bleakest job forecasts as an outlier scenario

Anthropic published an economic model with three US economic scenarios through 2030, framing CEO Dario Amodei's bleakest job-loss forecasts as the outlier outcome.

Anthropic released an economic model outlining three scenarios for AI's impact on the US economy through 2030. The modest scenario resembles the internet's impact with stable wages, the middle scenario doubles growth while knowledge worker wages stagnate, and the extreme scenario projects 17.9% knowledge worker unemployment with labor's GDP share falling from 60% to 45%. CEO Dario Amodei's May 2025 warning of up to half of entry-level office jobs vanishing and 10-20% unemployment aligns with the extreme scenario, which the model treats as the least likely outcome.

The Decoder · 7d agoAI industry2

Evaluating Time-Series Foundation Models and Multimodal Dietary Context for CGM Forecasting

Study finds zero-shot time-series foundation models underperform on CGM forecasting; fine-tuned Chronos-Bolt cuts RMSE up to 18.4% and dietary context adds signal.

The paper evaluates time-series foundation models for continuous glucose monitoring forecasting across eight public datasets covering Type 1 diabetes, Type 2 diabetes, and non-diabetes populations. Under a unified protocol, zero-shot foundation models did not consistently outperform baselines like Elastic Net and PatchTST, but lightweight fine-tuning did, with fine-tuned Chronos-Bolt reducing RMSE by 6.5%-18.4% in the T1D cohort and 8.6%-18.2% in the non-diabetes/T2D cohort. A residual-based fusion framework adding dietary context from CGMacros reduced overall RMSE by about 3% and postprandial RMSE by about 15% versus CGM-only baselines.

arXiv cs.AI / cs.LG / cs.CL · 6d agoAI research

The Frontier AEO Tracker: What Astra Chooses (and every other frontier model, and what you can do about it)

Latent Space launches an AEO tracker scoring 7 frontier models' product recommendations across 161 categories, revealing generational bias flips.

Latent Space built a tracker measuring Answer Engine Optimization by running 6 prompt variations across 7 frontier models with search enabled over 161 product categories, scoring first choices, alternatives, mentions, and anti-recommendations. It found 28 categories with a universally dominant primary choice and observed soft biases, such as models favoring their own lab's coding agents. Analysis of Anthropic's Sol→Astra and Opus→Fable generations showed newer models consulting fewer sources and being less likely to change answers when questions are paraphrased.

Latent Space · 9d agoAI research

How Zapier transformed core marketing processes with ChatGPT Work

Zapier's enterprise marketing team uses ChatGPT Work to cut lead-funnel drop-offs and automate reporting.

OpenAI published a customer story on how Zapier's enterprise marketing team adopted ChatGPT Work. Use cases include reducing lead funnel drop-offs, building campaign assets, and automating reporting. This is marketing case-study content rather than a product or research announcement.

OpenAI News · Aug 10, 2026AI industry

Is Cyber Facing an Affordability Crisis?

Dark Reading analysis argues record breach costs and roughly $240 billion in cyber defense spending leave small businesses dangerously exposed, threatening supply chains.

The analysis examines an affordability crisis in cybersecurity, noting breach costs have reached record highs while defense spending approaches $240 billion. It argues small businesses are dangerously under-protected relative to rising attack costs. Weak small-business defenses are framed as a supply chain security risk for larger organizations.

Dark Reading · 22d agoIndustry

Reimagining advertising with AI

OpenAI launches ChatGPT advertising features including Sponsored Agents, AI ad creation in Ads Manager, and integrations with HubSpot and Shopify.

OpenAI is testing Sponsored Agents in the United States, letting users converse with clearly labeled business-sponsored agents after clicking ads in ChatGPT. Advertisers can create, update, and analyze campaigns via natural-language prompts in ChatGPT with an Ads Manager plugin, plus AI-suggested copy and imagery in Ads Manager. HubSpot becomes the first CRM partner and Shopify the first ecommerce partner, with the Shopify app expanding internationally on September 23.

OpenAI News · 21h agoAI industry

Opaque recurrence, and other AI terms that you should probably know

TechCrunch updates its plain-English glossary defining common AI terms from AGI and agents to chain-of-thought reasoning.

TechCrunch maintains a regularly updated glossary of AI terminology, defining terms such as AGI, AI agents, API endpoints, chain of thought, coding agents, compute, deep learning, and diffusion. It highlights 'opaque recurrence', the reasoning technique in OpenAI's new Astra model that has drawn attention from AI safety researchers. The piece is an educational living document rather than new research or a product announcement.

TechCrunch · AI · 9d agoAI industry1