Throughout history, the ambition of technological advancement has always been driven by the pursuit of human prosperity. But with AI, we are approaching a pivotal gut check to live up to this promise for the next generation. In my role as CTO at SAS, I talk with a lot of […] The post Human prosperity […]
When I first started as a data scientist, there was a gap. I met with dozens of organizations who would invest time and resources into building accurate and tuned models and then ask, “What now?” They had a fantastic model in hand but couldn’t get it into a place and […] The post There is
Meta researchers have introduced Perception Encoder Audiovisual, PEAV, as a new family of encoders for joint audio and video understanding. The model learns aligned audio, video, and text representations in a single embedding space using large scale contrastive training on about 100M audio video pairs with text captions. From Perception Encoder to PEAV Perception Encoder,
«AutoQML, self-assembling circuits, hyper-parameterized Quantum ML platform, using cirq, tensorflow and tfq. Trillions of possible qubit registries, gate combinations and moment sequences, ready to be adapted into your ML flow. Here I demonstrate climatechange, jameswebbspacetelescope and microbiology vision applications… [Thus far, a circuit with 16-Qubits and a gate sequence of [ YY ] – [ XX ] – [CNOT]
Machine learning covers a lot of ground but it is also capable of making bad decision. We’ve also reached a stage of hype that folks forget that many classification problems can be handled by natural intelligence too. This package contains scikit-learn compatible tools that should make it easier to construct and benchmark rule based systems
Google has released T5Gemma 2, a family of open encoder-decoder Transformer checkpoints built by adapting Gemma 3 pretrained weights into an encoder-decoder layout, then continuing pretraining with the UL2 objective. The release is pretrained only, intended for developers to post-train for specific tasks, and Google explicitly notes it is not releasing post-trained or IT checkpoints
Small language models like GLiNER provide an efficient, deterministic, and flexible solution for named entity recognition, bridging the gap between traditional NLP and large language models for enterprise information extraction. The post The rise of small language models for information extraction appeared first on SAS Blogs.
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Generative AI has seen drastic improvement in image, video, audio, and text generation within the last few years. Humans, on the other hand, are still catching up on determining when it’s appropriate to use Generative AI and how to review the content generated by AI before sharing it with others. […] The post No one
In this tutorial, we explore how we design and run a full agentic AI orchestration pipeline powered by semantic routing, symbolic guardrails, and self-correction loops using Gemini. We walk through how we structure agents, dispatch tasks, enforce constraints, and refine outputs using a clean, modular architecture. As we progress through each snippet, we see how
혁신적인 합성 데이터 생성 솔루션으로 데이터 부족 문제 해결, AI 역량 강화 마이크로소프트 마켓플레이스에서 우선 공급 민감한 개인정보를 노출하지 않으면서 안전하게 합성 데이터를 생성할 수 있게 해주는 ‘SAS 데이터 메이커’가 출시되었습니다. 현재 마이크로소프트 마켓플레이스에서 제공되는 ‘SAS 데이터 메이커’는 실제 데이터의 통계적, 관계적, 시간적 특성을 그대로 재현하는 합성 데이터를 생성하며, […] The post 엔터프라이즈 합성
