In high-stakes settings such as medical diagnostics, users often want to know what prompted a computer vision model to make a particular prediction, so they can decide whether or not to trust its output. Conceptual bottleneck modeling is one way…
Louisville, Kentucky, and Ahmedabad, India, February 22, 2026 — Shaip, a leading AI data platform and services provider that delivers high-quality, ethical, domain-specific data for AI development and large language models (LLM), today announced that it is now part of…
On February 17 at 12pm EST, we hosted a live session titled From concept to production: Build AI products quickly without hiring a huge team. In this conversation, our experts from Fusemachines, Jeffrey Kielholtz (Director of AI Solutions), and Robert…
Introduction Since late 2025, the generative AI landscape has exploded with new releases. OpenAI’s GPT‑5.2, Anthropic’s Claude Opus 4.6, Google’s Gemini 3.1 Pro and MiniMax’s M2.5 signal a turning point: models are no longer one‑size‑fits‑all tools but specialized engines optimized…
In today’s digital workplace, technology is the backbone of productivity. Employees rely on IT systems to communicate, collaborate, access data, and manage tasks. This makes IT Service Management (ITSM) A critical function within every organization. ITSM refers to the structured…
Many engineering challenges lead to the same headache, which is having too many knobs to turn and too few opportunities to test them. Whether adjusting a power grid or designing a safer car, each evaluation can be expensive, and there…
Many smart devices now have a built-in virtual assistant that uses ASR technology to process voice commands, such as “set alarm,” “create reminders with AI,” and “listen to music.” From video caption generators and voice search to the development of…
This post contains a list of AI-related seminars scheduled to take place between March 2 and April 30, 2026. All events detailed here are free and open for anyone to attend virtually. March 2, 2026 Three talks: 1) Explaining deviations…
As artificial intelligence (AI) and the Internet of Things (IoT) accelerate the pace of discovery, research teams are facing an unprecedented increase in the volume, velocity, and complexity of data. What used to be validated through manual checks now includes…
The current path of generative AI relies heavily on Latent Diffusion Models (LDMs) To manage the computational cost of high-resolution synthesis. By compressing data into a lower-dimensional latent space, models can scale effectively. However, a fundamental trade-off remains: lower information…
Customizing large language models (LLMs) currently represents an important engineering trade-off between flexibility In-context learning (ICL) And efficiency Context Distillation (CD) or Supervised Fine Tuning (SFT). Tokyo-based Sakana AI has proposed a new approach to bypass these limitations through cost…
AI doesn’t just add work; It changes work in ways that are now empirically undeniable. Harvard Business Review articleArtificial intelligence does not reduce work, it intensifies it“Confirms the validity of what I call”Artificial intelligence taxAlmost a year ago: AI increases…
