Snowflake (NYSE: SNOW), the Data Cloud company, today announced
Snowflake Arctic, a state-of-the-art large language model (LLM)
uniquely designed to be the most open, enterprise-grade LLM on the
market. With its unique Mixture-of-Experts (MoE) architecture,
Arctic delivers top-tier intelligence with unparalleled efficiency
at scale. It is optimized for complex enterprise workloads, topping
several industry benchmarks across SQL code generation, instruction
following, and more. In addition, Snowflake is releasing Arctic’s
weights under an Apache 2.0 license and details of the research
leading to how it was trained, setting a new openness standard for
enterprise AI technology. The Snowflake Arctic LLM is a part of the
Snowflake Arctic model family, a family of models built by
Snowflake that also include the best practical text-embedding
models for retrieval use cases.
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the full release here:
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Snowflake Arctic adds truly open large
language model with unmatched intelligence and efficiency to the
Snowflake Arctic model family (Graphic: Business Wire)
“This is a watershed moment for Snowflake, with our AI research
team innovating at the forefront of AI,” said Sridhar Ramaswamy,
CEO, Snowflake. “By delivering industry-leading intelligence and
efficiency in a truly open way to the AI community, we are
furthering the frontiers of what open source AI can do. Our
research with Arctic will significantly enhance our capability to
deliver reliable, efficient AI to our customers.”
Arctic Breaks Ground With Truly Open, Widely Available
Collaboration
According to a recent report by Forrester, approximately 46
percent of global enterprise AI decision-makers noted that they are
leveraging existing open source LLMs to adopt generative AI as a
part of their organization’s AI strategy.1
With Snowflake as the data foundation to more than 9,400 companies
and organizations around the world2, it is
empowering all users to leverage their data with industry-leading
open LLMs, while offering them flexibility and choice with what
models they work with.
Now with the launch of Arctic, Snowflake is delivering a
powerful, truly open model with an Apache 2.0 license that permits
ungated personal, research, and commercial use. Taking it one step
further, Snowflake also provides code templates, alongside flexible
inference and training options so users can quickly get started
with deploying and customizing Arctic using their preferred
frameworks. These will include NVIDIA NIM with NVIDIA
TensorRT-LLM, vLLM, and Hugging Face. For
immediate use, Arctic is available for serverless inference in
Snowflake Cortex, Snowflake’s fully managed service that
offers machine learning and AI solutions in the Data Cloud. It will
also be available on Amazon Web Services (AWS), alongside
other model gardens and catalogs, which will include Hugging
Face, Lamini, Microsoft Azure, NVIDIA API
catalog, Perplexity, Together AI, and more.
Arctic Provides Top-Tier Intelligence with Leading
Resource-Efficiency
Snowflake's AI research team, which includes a unique
composition of industry-leading researchers and system engineers,
took less than three months and spent roughly one-eighth of the
training cost of similar models when building Arctic. Trained using
Amazon Elastic Compute Cloud (Amazon EC2) P5 instances, Snowflake
is setting a new baseline for how fast state-of-the-art open,
enterprise-grade models can be trained, ultimately enabling users
to create cost-efficient custom models at scale.
As a part of this strategic effort, Arctic’s differentiated MoE
design improves both training systems and model performance, with a
meticulously designed data composition focused on enterprise needs.
Arctic also delivers high-quality results, activating 17 out of 480
billion parameters at a time to achieve industry-leading quality
with unprecedented token efficiency. In an efficiency breakthrough,
Arctic activates roughly 50 percent less parameters than DBRX, and
75 percent less than Llama 3 70B during inference or training. In
addition, it outperforms leading open models including DBRX,
Mixtral-8x7B, and more in coding (HumanEval+, MBPP+) and SQL
generation (Spider), while simultaneously providing leading
performance in general language understanding (MMLU).
Snowflake Continues to Accelerate AI Innovation for All
Users
Snowflake continues to provide enterprises with the data
foundation and cutting-edge AI building blocks they need to create
powerful AI and machine learning apps with their enterprise data.
When accessed in Snowflake Cortex, Arctic will accelerate
customers’ ability to build production-grade AI apps at scale,
within the security and governance perimeter of the Data Cloud.
In addition to the Arctic LLM, the Snowflake Arctic family of
models also includes the recently announced Arctic embed, a family
of state-of-the-art text embedding models available to the open
source community under an Apache 2.0 license. The family of five
models are available on Hugging Face for immediate use and will
soon be available as part of the Snowflake Cortex embed function
(in private preview). These embedding models are optimized to
deliver leading retrieval performance at roughly a third of the
size of comparable models, giving organizations a powerful and
cost-effective solution when combining proprietary datasets with
LLMs as part of a Retrieval Augmented Generation or semantic search
service.
Snowflake also prioritizes giving customers access to the newest
and most powerful LLMs in the Data Cloud, including the recent
additions of Reka and Mistral AI’s models. Moreover, Snowflake
recently announced an expanded partnership with NVIDIA to continue
its AI innovation, bringing together the full-stack NVIDIA
accelerated platform with Snowflake’s Data Cloud to deliver a
secure and formidable combination of infrastructure and compute
capabilities to unlock AI productivity. Snowflake Ventures has also
recently invested in Landing AI, Mistral AI, Reka, and more to
further Snowflake’s commitment to helping customers create value
from their enterprise data with LLMs and AI.
Comments On the News from AI Experts
“Snowflake Arctic is poised to drive significant outcomes that
extend our strategic partnership, driving AI access,
democratization, and innovation for all,” said Yoav Shoham,
Co-Founder and Co-CEO, AI21 Labs. “We are excited to see
Snowflake help enterprises harness the power of open source models,
as we did with our recent release of Jamba — the first
production-grade Mamba-based Transformer-SSM model. Snowflake’s
continued AI investment is an important factor in our choosing to
build on the Data Cloud, and we’re looking forward to continuing to
create increased value for our joint customers.”
“Snowflake and AWS are aligned in the belief that generative AI
will transform virtually every customer experience we know,” said
David Brown, Vice President Compute and Networking, AWS.
"With AWS, Snowflake was able to customize its infrastructure to
accelerate time-to-market for training Snowflake Arctic. Using
Amazon EC2 P5 instances with Snowflake’s efficient training system
and model architecture co-design, Snowflake was able to quickly
develop and deliver a new, enterprise-grade model to customers. And
with plans to make Snowflake Arctic available on AWS, customers
will have greater choice to leverage powerful AI technology to
accelerate their transformation.”
“As the pace of AI continues to accelerate, Snowflake has
cemented itself as an AI innovator with the launch of Snowflake
Arctic,” said Shishir Mehrotra, Co-Founder and CEO, Coda.
“Our innovation and design principles are in-line with Snowflake’s
forward-thinking approach to AI and beyond, and we’re excited to be
a partner on this journey of transforming everyday apps and
workflows through AI.”
“There has been a massive wave of open-source AI in the past few
months,” said Clement Delangue, CEO and Co-Founder, Hugging
Face. “We're excited to see Snowflake contributing
significantly with this release not only of the model with an
Apache 2.0 license but also with details on how it was trained. It
gives the necessary transparency and control for enterprises to
build AI and for the field as a whole to break new grounds.”
“Lamini's vision is to democratize AI, empowering everyone to
build their own superintelligence. We believe the future of
enterprise AI is to build on the foundations of powerful open
models and open collaboration," said Sharon Zhou, Co-Founder and
CEO, Lamini. “Snowflake Arctic is important to supporting
that AI future. We are excited to tune and customize Arctic for
highly accurate LLMs, optimizing for control, safety, and
resilience to a dynamic AI ecosystem.”
“Community contributions are key in unlocking AI innovation and
creating value for everyone,” said Andrew Ng, CEO, Landing
AI. “Snowflake’s open source release of Arctic is an exciting
step for making cutting-edge models available to everyone to
fine-tune, evaluate and innovate on.”
“We’re pleased to increase enterprise customer choice in the
rapidly evolving AI landscape by bringing the robust capabilities
of Snowflake’s new LLM model Arctic to the Microsoft Azure AI model
catalog,” said Eric Boyd, Corporate Vice President, Azure AI
Platform, Microsoft. “Our collaboration with Snowflake is an
example of our commitment to driving open innovation and expanding
the boundaries of what AI can accomplish.”
“The continued advancement — and healthy competition between —
open source AI models is pivotal not only to the success of
Perplexity, but the future of democratizing generative AI for all,”
said Aravind Srinivas, Co-Founder and CEO, Perplexity. “We
look forward to experimenting with Snowflake Arctic to customize it
for our product, ultimately generating even greater value for our
end users.”
“Snowflake and Reka are committed to getting AI into the hands
of every user, regardless of their technical expertise, to drive
business outcomes faster,” said Dani Yogatama, Co-Founder and CEO,
Reka. “With the launch of Snowflake Arctic, Snowflake is
furthering this vision by putting world-class truly-open large
language models at users’ fingertips.”
“As an organization at the forefront of open source AI research,
models, and datasets, we’re thrilled to witness the launch of
Snowflake Arctic,” said Vipul Ved Prakash, Co-Founder and CEO,
Together AI. “Advancements across the open source AI
landscape benefit the entire ecosystem, and empower developers and
researchers across the globe to deploy impactful generative AI
models.”
Learn More:
- Register for Snowflake Data Cloud Summit 2024, June 3-6, 2024
in San Francisco, to get the latest on Snowflake’s AI
announcements, and check out Snowflake Dev Day on June 6, 2024 to
see these innovations in action.
- Users can go to Hugging Face to directly download Snowflake
Arctic and use Snowflake’s Github repo for inference and
fine-tuning recipes.
- Get more information and additional resources on Snowflake
Arctic, here.
- Dig into how the Snowflake AI research team trained Snowflake
Arctic in this blog.
- See how organizations are bringing generative AI and LLMs to
their enterprise data in this video.
- Stay on top of the latest news and announcements from Snowflake
on LinkedIn and Twitter.
1The State of Generative AI, Forrester
Research Inc., January 26, 2024.
2 As of January 31, 2024.
About Snowflake
Snowflake makes enterprise AI easy, efficient, and trusted.
Thousands of companies around the globe, including hundreds of the
world’s largest, use Snowflake’s Data Cloud to share data, build AI
and machine learning applications, and power their business. The
era of enterprise AI is here. Learn more at snowflake.com (NYSE:
SNOW).
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version on businesswire.com: https://www.businesswire.com/news/home/20240424761970/en/
Kaitlyn Hopkins
Senior Product PR Lead, Snowflake
press@snowflake.com
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