forecasting
30 articles about forecasting in AI news
New Research: Fine-Tuned LLMs Outperform GPT-5 for Probabilistic Supply Chain Forecasting
Researchers introduced an end-to-end framework that fine-tunes large language models (LLMs) to produce calibrated probabilistic forecasts of supply chain disruptions. The model, trained on realized outcomes, significantly outperforms strong baselines like GPT-5 on accuracy, calibration, and precision. This suggests a pathway for creating domain-specific forecasting models that generate actionable, decision-ready signals.
Google Open-Sources TimesFM: A 100B-Point Time Series Foundation Model for Zero-Shot Forecasting
Google has open-sourced TimesFM, a foundation model for time series forecasting trained on 100 billion real-world time points. It requires no dataset-specific training and can generate predictions instantly for domains like traffic, weather, and demand.
How AI is Impacting Five Demand Forecasting Roles in Retail
AI is transforming demand forecasting, shifting roles from manual data processing to strategic analysis. The article identifies five key positions being reshaped, highlighting a move towards higher-value, AI-augmented work.
Smarter Shopping: Forecasting the Future of AI Agents in Retail
The Wall Street Journal reports on the emerging role of autonomous AI agents in retail, forecasting their potential to transform shopping by handling complex, multi-step tasks. This signals a shift from passive chatbots to active, goal-oriented assistants.
New Research Identifies Data Quality as Key Bottleneck in Multimodal Forecasting
A new arXiv paper introduces CAF-7M, a 7-million-sample dataset for context-aided forecasting. The research shows that poor context quality, not model architecture, has limited multimodal forecasting performance. This has implications for retail demand prediction that combines numerical data with text or image context.
TimeSqueeze: A New Method for Dynamic Patching in Time Series Forecasting
Researchers introduce TimeSqueeze, a dynamic patching mechanism for Transformer-based time series models. It adaptively segments sequences based on signal complexity, achieving up to 20x faster convergence and 8x higher data efficiency. This addresses a core trade-off between accuracy and computational cost in long-horizon forecasting.
Beyond Simple Predictions: How Frequency Domain AI Transforms Retail Demand Forecasting
New FreST Loss AI technique analyzes retail data in joint spatio-temporal frequency domain, capturing complex dependencies between stores, products, and time for superior demand forecasting accuracy.
TimeGS: How Computer Graphics Techniques Are Revolutionizing Time Series Forecasting
Researchers have introduced TimeGS, a novel AI framework that treats time series forecasting as a 2D rendering problem. By adapting Gaussian splatting techniques from computer graphics, the approach achieves state-of-the-art performance while maintaining temporal continuity.
StaTS AI Model Revolutionizes Time Series Forecasting with Adaptive Noise Schedules
Researchers introduce StaTS, a diffusion model that learns adaptive noise schedules and uses frequency guidance for superior time series forecasting. The approach addresses key limitations in existing methods while maintaining efficiency.
Google's TimesFM Foundation Model: A New Paradigm for Time Series Forecasting
Google Research has open-sourced TimesFM, a 200 million parameter foundation model for time series forecasting. Trained on 100 billion real-world time points, it demonstrates remarkable zero-shot forecasting capabilities across diverse domains without task-specific training.
AI-Powered Geopolitical Forecasting: How Machine Learning Models Are Predicting Regime Stability
Advanced AI systems are now analyzing political instability with unprecedented accuracy, predicting regime vulnerabilities in real-time. These models process vast datasets to forecast governmental collapse and potential conflict escalation.
OpenAI Forecasts $121B in AI Hardware Costs for 2028
OpenAI is forecasting its own AI research hardware costs will reach $121 billion in 2028, according to a WSJ report. This figure highlights the extreme capital intensity required to compete at the frontier of AI.
Kronos AI Outperforms Leading Time Series Models by 93% on Candlestick Data
Researchers from Tsinghua University released Kronos, an open-source foundation model trained on 12 billion candlestick records from 45 exchanges. It reportedly achieves 93% higher accuracy than leading time series models for price and volatility forecasting, requiring no fine-tuning.
Google's TimesFM: 200M-Param Foundation Model for Zero-Shot Time Series
Google released TimesFM, a 200M-parameter foundation model for time series forecasting that works without training on user data. It's now available open-source and as a product inside BigQuery.
AI-2027 Authors Accelerate AGI Timelines, Citing Rapid Progress in Agentic Coding
The AI-2027 forecasting group has accelerated its timeline for when AI could replace human software engineers by 1.5 years, from late 2029 to mid-2028. This revision is based on observed rapid progress in agentic coding systems over the last 3-5 months.
Beyond Blue Books: How Real-Time Market Intelligence AI is Transforming Luxury Asset Valuation
duPont REGISTRY Group's deployment of real-time AI analytics for luxury vehicles demonstrates a scalable model for dynamic pricing, authentication, and market forecasting of high-value collectibles. This approach directly translates to luxury retail for limited editions, vintage items, and exclusive collections.
Google's TimesFM: The Zero-Shot Time Series Model That Works Without Training
Google has open-sourced TimesFM, a foundation model for time series forecasting that requires no training on specific datasets. Unlike traditional models, it can make predictions directly from historical data, potentially revolutionizing forecasting across industries.
Albertsons Launches AI Supply Chain Tool With Computer Vision
Albertsons launched a patent-pending AI supply chain tool using computer vision to reduce food waste and improve inventory across 2,200+ stores.
Amazon Now Expands 30-Minute Delivery to 8 More US Cities
Amazon expands Amazon Now 30-minute delivery to 8 new cities, targeting tens of millions by end of 2026. Prime members pay $3.99 per order.
Prithvi-EO Fails Cross-Country Crop Yield Generalization, Paper Shows
Prithvi-EO and ViT-Base embeddings yield universally negative R² under cross-country maize yield prediction, failing to beat traditional spectral features due to yield distribution shift.
Build Reusable Data Science Workflows with Claude Skills and Subagents
Claude Skills and Subagents let you package prompts into reusable modules, freeing data scientists from repetitive AI adjustments for EDA, modeling, and deployment.
Grocery Dive Asks: Is Agentic AI the Next Frontier for Grocers?
The article examines agentic AI's potential for grocers in inventory, personalization, and store operations, weighing benefits against implementation challenges like data integration and safety.
Why Production AI Needs More Than Benchmark Scores
The article argues that high benchmark scores are insufficient for production AI success, highlighting the need for robust MLOps practices, monitoring, and real-world testing—critical for retail applications.
Castore and GXO Detail 'Sustainable Scale' Strategy at Drapers Supply
At the Drapers Supply Chain Summit, Castore CSCO Adrian Harris detailed how the rapid-growth sportswear brand is shifting focus from breakneck expansion to 'sustainable scale' with logistics partner GXO. The partnership is central to operationalizing sustainability in Castore's supply chain.
Guerlain Launches First Paid Influencer Campaign After Viral TikTok
Guerlain reports the Vanille Planifolia extrait became its #1 best-selling product for five months after organic TikTok videos, leading to the brand’s first paid influencer campaign. Sales tripled despite the $660 price, and the fragrance sold out multiple times.
Why AI and luxury retail go hand-in-hand — The Drum article explores the synergy
A new article from The Drum examines how artificial intelligence can enhance luxury retail experiences without diluting brand prestige. The exact arguments and examples are not accessible from the snippet.
Chief AI & Technology Officer Role Gains Traction in Luxury Sector
The luxury sector is formalizing AI leadership by establishing Chief AI and Technology Officer positions. This move reflects the industry's transition from ad-hoc AI initiatives to integrated, strategic technology governance at the highest level.
Microsoft, Google Shift to Range-Based AI Capacity Planning at DC World 2026
At Data Center World 2026, Microsoft and Google revealed they've shifted from point forecasts to range-based planning for AI workloads, with weekly reviews and modular infrastructure to absorb demand volatility.
AI Turned Thrift Into a Profitable Fashion Machine
The article details how AI technologies are being deployed in the thrift and resale fashion industry to automate critical operations like pricing, authentication, and inventory management, turning a traditionally labor-intensive sector into a scalable, data-driven profit engine.
Airbnb's Engineering Blueprint for a Petabyte-Scale
Airbnb engineers detail the construction of a massive, internally operated metrics storage system. The system ingests 50 million samples per second, manages 1.3 billion active time series, and stores 2.5 petabytes of data, overcoming challenges in tenancy, shuffle sharding, and observability at scale.