Copy That: Teaching AI to Speak the Right Language
Scalable approach to creating higher-quality AI content—improving accuracy and strengthening client relationships.
Showcasing practical applications of newly published AI research—empowering you to seize your first-mover advantage.
Scalable approach to creating higher-quality AI content—improving accuracy and strengthening client relationships.
A practical framework for adapting existing video AI models into short-horizon forecasting tools—driving smarter, safer, and more proactive operations.
A smarter approach to AI decision-making reveals how broader tool usage drives better results across complex, multi-step customer interactions.
Reframing data privacy as a measurable risk can improve decision-making, model performance, and customer trust.
How rethinking motion data can reduce risk, improve performance forecasting, and future-proof decision-making.
How dynamic, AI-driven simulations can transform long-range transit planning and improve rider satisfaction at scale.
A strategic approach to reducing abandonment, boosting accuracy, and rebuilding trust with smarter spatial AI.
How cognitive modeling helps uncover and adjust the hidden value trade-offs in AI language systems—improving clarity, trust, and control.
A new approach to AI decision-making helps organizations balance speed with discernment—deferring ambiguous cases to human experts.
A case study in designing AI to reason selectively—investing more effort only when human fairness would demand it.
How narrative-based AI workflows can unlock deeper emotional insight, improve employee engagement, and deliver more meaningful feedback loops.
Learn how structured oversight transforms model transparency from a bottleneck into a competitive advantage.
Predictive learning from video is helping automation systems understand physical environments and adapt to new tasks.
Why AI agents struggle with complex procedures (and how rethinking workflows unlocks reliable, scalable automation).
A practical framework for implementing scalable, benchmarked AI agents that reason, adapt, and deliver high-impact CX.
Adaptive routing strategies help autonomous systems manage congestion, reduce delays, and scale operations without centralized control.
Extended reinforcement learning reveals new strategies for training AI systems to detect and respond to complex, multi-stage problems.
Why the future of AI-assisted tools depends on solving long-context reasoning (and how forward-thinking teams are already getting it right).
A strategic guide to overcoming visual realism limits with scalable, intelligent rendering pipelines for immersive applications.
A scalable approach to long-form content that balances originality, efficiency, and editorial integrity.
DSMentor shows how sequencing and memory can unlock more reliable, transparent, and strategic AI performance.
How a multi-agent AI and LLM framework like Vaiage unlocks smarter, scalable planning systems for unpredictable customer experiences.
MegaBeam‑Mistral‑7B processes entire reports in one pass—streamlining audits and improving cross‑reference checks.
Enforce structured, machine-readable outputs from LLMs, without sacrificing flexibility or retraining existing systems.
Layered Safe MARL offers a breakthrough in managing multi-agent conflict without compromising performance or safety.
How verifiable AI and the HalluMix framework can help build trustworthy coding assistants and reduce hallucinated outputs
A new approach to model training helps AI generalize better, adapt faster, and scale more effectively across unpredictable use cases.
How PSA is helping organizations move faster by transforming vague AI ambitions into clear, actionable project definitions.
How autoencoder-enabled filters and KD models strengthen FL against model poisoning threats.
Harnessing CLIMB to systematically improve AI performance and efficiency through strategic training data optimization.
Rethinking multilingual LLM evaluation to improve accuracy, reduce risk, and scale client experiences in every language.
InternVL3 enables smarter, faster decisions by combining vision and language processing—unlocking scalable efficiency.
How native multimodal models are transforming AI by unifying data types, reducing system complexity, and accelerating product innovation.
Leveraging BLUR to transform fuzzy customer inputs into clear results by building AI systems that reason, browse, and adapt like humans.
Detecting AI-generated content using sparse autoencoders to protect trust, transparency, and competitive edge in the age of AI authorship.
SmolLM2 delivers scalable AI performance in constrained environments—helping teams innovate faster with efficient, focused models.