We’re excited to announce that our new course, ‘Build Long Context AI Apps with Jamba’, built in partnership with @AndrewYNg @DeepLearningAI is now live – and it’s currently free! In this course, Chen Wang and Chen Almagor from AI21 Labs will walk you through how to use
@ai21labs
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AI21 Labs Warns Against Fraudulent Cryptocurrency Scams
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We are warning about scams being perpetrated by malicious actors falsely claiming to be AI21-related crypto/tokens. We explicitly clarify: AI21 has absolutely no connection, direct or indirect, to any cryptocurrency or tokens whatsoever. These cases have been reported to X and
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Jamba 1.5: Balancing Speed and Quality Efficiency
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But our cost, efficiency and speed don't come at the expense of quality. In the following chart, Jamba 1.5 Large and Mini both show a great balance between speed and quality (QI is where you want to be). >>
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Jamba Architecture Optimizes Speed-Cost-Quality Triangle
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High throughput itself is never enough; it's all about optimizing the speed-cost-quality triangle. Thanks to Jamba’s architecture, we offer high speed at a very competitive price (in the image below, QII is where you want to be). >>
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Jamba 1.5 Models Demonstrate Significantly Superior Throughput Performance
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We know that Jamba 1.5 models are the fastest, but the question is – how fast? @ArtificialAnlys tested our models to find out The image below shows the throughput for various models (with prompt length = 10K tokens). Jamba 1.5 models are a whole lot faster – and that speed
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Jamba 1.5 Model Family Now Available on Google Cloud Vertex AI
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Introducing the Jamba 1.5 Model Family on @googlecloud
's Vertex AI: – Simplify development and evaluation with advanced tools and intuitive API calls.
– Focus on innovation with fully managed infrastructure and cost-effective, pay-as-you-go pricing.
– Ensure data security with -
AI21 Labs Jamba 1.5 Models Optimized for Agent Creation
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Our team had a blast at the @agihouse_org agents hackathon yesterday in the Bay Area with @langchain
, @GroqInc , @DeepLearningAI & @AndrewYNg
. Our new Jamba 1.5 models are optimized for agent creation with a ton of built in features like:
– Function calling
– Structured JSON -
Jamba Architecture Advantages in Long Context Fine-Tuning Efficiency
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We found our efficient Jamba architecture to be advantageous in long context fine-tuning, as it allows for greater speed and lower cost. Therefore, we could experiment with multiple different training recipes during the fine-tuning phase. This is especially interesting for all
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Jamba-1.5 Models Demonstrate Strong Multilingual Performance Despite Limited Post-Training Data
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Jamba-1.5 models perform well in multiple languages, even though we include only a very small fraction of non-english data in the post-training phase. Therefore, we speculate the models are able to use the learned multilingual capabilities from the pre-training phase. 6/7