vasudevlal
@vasudev_lal
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Joined June 2021
Ever wanted to learn how to create exciting Multimodal RAG applications using Large Vision-Language Models? Take this course and learn how you can build an interactive app that allows you to "Chat with Videos".
New short course Multimodal RAG: Chat with Videos, developed with @intel and taught by @vasudev_lal!. In this course, you’ll work with LLaVA (Large Language and Vision Assistant), a Large Vision Language Model (LVLM) that can process both images and text. For example, given an
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RT @AndrewYNg: New short course Multimodal RAG: Chat with Videos, developed with @intel and taught by @vasudev_lal!. In this course, you’ll….
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RT @IntelAI: Our own @vasudev_lal highlights RAG's role in advancing AI with less effort. RAG enables smarter, data-driven AI outputs witho….
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RT @RisingSayak: Getting that cat "next" to a suitcase seems to be always a problem for T2I diffusion models 🤷♂️. In our latest work, we i….
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RT @iScienceLuvr: LDM3D-VR: Latent Diffusion Model for 3D VR. abs: This paper from Intel Labs introduces a suite o….
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Extremely proud that our paper (LDM3D-VR) Latent Diffusion Model for 3D VR was featured by @_akhaliq in @huggingface's "Daily Papers" selection for Nov 7. Check out the paper!.
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RT @danielnewmanUV: Intel based accelerators deliver 2.5x permanece over $NVDA A100 and 1.4x over the H1 on @huggingface vision language mo….
huggingface.co
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RT @GisreRegis: We just released a new benchmark where @HabanaLabs Gaudi2 is up to x1.4 faster than Nvidia H100!.x1.2 speedup with the exac….
huggingface.co
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RT @swabhz: How can we build better counterfactuals for data augmentation?. Check out our #emnlp2022 paper: "NeuroCounterfactuals: Beyond M….
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RT @intelnews: Have you ever wanted to create your own world?. Intel and Blockade Labs are using #GenerativeAI to make immersive 360-degree….
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RT @BlockadeLabs: In collaboration with @Intel, our Depth Fusion showcases the power of our LDM3D diffusion model in generating 360° views….
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RT @yoavgo: congrats to @AmirDNC and @SRosenamn for winning the best paper award at AKBC 2022! (for a paper that was previously rejected fr….
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RT @jerryptang: very excited to share our paper on reconstructing language from non-invasive brain recordings! we introduce a decoder that….
biorxiv.org
A brain-computer interface that decodes continuous language from non-invasive recordings would have many scientific and practical applications. Currently, however, decoders that reconstruct continu...
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RT @_akhaliq: VL-InterpreT: An Interactive Visualization Tool for Interpreting Vision-Language Transformers.abs: ht….
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RT @humphrey_shi: Best Demo Award #2:.VL-InterpreT: An Interactive Visualization Tool for Interpreting Vision-Language Transformers by @_du….
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RT @Plinz: From attention to consciousness: Michael Graziano, Jonathan Cohen, Vasudev Lal and me will discuss about attention models in phi….
eventbrite.com
A panel discussion on models of attention in the context of machine learning, cognitive science and the future developments of AI.
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RT @sandyasm: #nlproc we have a stellar list of speakers for #kinn2021 #cikm2021 workshop: @luislamb @rao2z @GaryMarcus @VeredShwartz @ABo….
sites.google.com
The availability of rich structured knowledge sources has spurred interest in exploring Knowledge Injection in Neural Networks (KINN) as a means of mitigating the challenges associated with current...
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