Last 3 Events | ||||
STHLM Machine Learning Club & A Bit of AI mini conference | Conference | 2022-05-17 | ||
Microsoft Build: Local Event Experience | Ceremony | 2022-05-24 | ||
Microsoft Envision Sweden: Experterna reder ut begreppen kring Open AI | Webinar | 2023-06-08 |
Den nya rapporten AI – en samhällsfråga för alla från Microsoft Sverige visar svenskarnas inställning till AI och hur attityderna till artificiell intelligens (AI) har förändrats under de senaste fem åren. Rapporten är en uppföljning av undersökningen AI är en samhällsfråga från AddAI och Novus från 2019, med uppdaterade perspektiv till följd av att svenskarnas syn på AI har utvecklats sedan generativ AI nu slagit igenom på bred front. ”Rapporten AI – en samhällsfråga för alla visar att medan AI erbjuder stora möjligheter för samhället, finns det också utmaningar och farhågor hos medborgarna som måste adresseras. Vårt mål på Microsoft är att fortsätta främja ansvarsfull innovation, kunskapsspridning och utbildning för att säkerställa att AI inte bara bidrar till ett mer konkurrenskraftigt Sverige, men att vi alla samtidigt känner oss trygga i den utvecklingen”, säger Daniel Akenine, Nationell teknikchef på Microsoft Sverige. |
We introduce VASA, a framework for generating lifelike talking faces of virtual charactors with appealing visual affective skills (VAS), given a single static image and a speech audio clip. Our premiere model, VASA-1, is capable of not only producing lip movements that are exquisitely synchronized with the audio, but also capturing a large spectrum of facial nuances and natural head motions that contribute to the perception of authenticity and liveliness. The core innovations include a holistic facial dynamics and head movement generation model that works in a face latent space, and the development of such an expressive and disentangled face latent space using videos. Through extensive experiments including evaluation on a set of new metrics, we show that our method significantly outperforms previous methods along various dimensions comprehensively. Our method not only delivers high video quality with realistic facial and head dynamics but also supports the online generation of 512x512 videos at up to 40 FPS with negligible starting latency. It paves the way for real-time engagements with lifelike avatars that emulate human conversational behaviors. |
As AI becomes more woven into society, its economic impact will be significant, and organizations are just starting to understand the extent of what’s possible. For companies to invest in AI though, it must make good business sense. Business leaders and decision makers need to understand the industry and line-of-business use cases that are best... |
Learn how to select and manage AI projects for business success – no engineering background or AI knowledge required. Whether you’re a business leader tasked with delivering results with AI or a data scientist who is business or leadership focused, read Succeeding with AI: How to make AI work for your business to learn how to bring AI to your organisation. Read the e-book to:
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A special event with Satya Nadella and Jared Spataro focused on how AI will power a whole new way of working for everyone. 0:00 - Satya Nadella announces new AI tool |
Tech giant Microsoft has unveiled a new AI training method called the "Algorithm of Thoughts" (AoT), designed to make large language models like ChatGPT more efficient and human-like in their reasoning abilities. Microsoft says the AoT technique is a potential game-changer, as it "guides the language model through a more streamlined problem-solving path," according to a published research paper. This novel approach utilizes "in-context learning," enabling the model to explore different solutions in an organized manner systematically. The result? Faster, less resource-intensive problem-solving. |
A big convergence of language, vision, and multimodal pretraining is emerging. In this work, we introduce a general-purpose multimodal foundation model BEIT-3, which achieves state-of-the-art transfer performance on both vision and vision- language tasks. Specifically, we advance the big convergence from three aspects: backbone architecture, pretraining task, and model scaling up. We introduce Multi- way Transformers for general-purpose modeling, where the modular architecture enables both deep fusion and modality-specific encoding. Based on the shared backbone, we perform masked “language” modeling on images (Imglish), texts (English), and image-text pairs (“parallel sentences”) in a unified manner. Exper- imental results show that BEIT-3 obtains state-of-the-art performance on object detection (COCO), semantic segmentation (ADE20K), image classification (Im- ageNet), visual reasoning (NLVR2), visual question answering (VQAv2), image captioning (COCO), and cross-modal retrieval (Flickr30K, COCO). |
Employees | ||
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Brian Lester | AI Change Agent | |
Jonn Mahlgård | Other role |