Meet our “Tiny Giant.” Our 1B parameter model xLAM-1B is now the best micro model for function calling, outperforming models 7x its size, including GPT-3.5 & Claude. On-device agentic AI is here.
#AIResearch
#SLM
#TinyButMighty
Paper:
Github:
Time-series forecasting methods perform poorly on long sequences when data changes over time. DeepTime overcomes this issue by using forecasting-as-meta-learning on deep time-index models. Result: state-of-the-art performance and a highly efficient model.
Our CodeGen models are now available at
@huggingface
! (Model size variants: 350M, 2B, 6B, and 16B.)
Clone the latest transformers repository and try it out!
Paper:
Models:
Releasing 🚀 CodeGen2.5 🚀, a small but mighty LLM for code.
- On par with models twice its size
- Trained on 1.5T tokens
- Features fast infill sampling
Blog:
Paper:
Code:
Model:
We’re thrilled to announce that Silvio Savarese (
@silviocinguetta
), former associate professor of Computer Science at Stanford University, has joined
@salesforce
as our new EVP and Chief Scientist of Salesforce Research!
Discover CodeGen - an AI model that turns simple natural-language requests into executable code. Learn more about this breakthrough in conversational AI programming.
Paper:
Blog:
Code:
🔥Introducing XGen-7B, a new 7B LLM trained on 8K seq. length for 1.5T tokens. Better or comparable results with MPT, Falcon, LLaMA, OpenLLaMA in text & code tasks.
Blog:
Code:
Training cost ~$150K for 1T token
🤩 📣 Announcing the 2nd Annual
@Salesforce
Research Deep Learning Grant 🤩 📣
We're looking for diverse individuals with innovative ideas who can join us in shaping the future of AI.
Apply today, and earn up to $50,000!
Did you know most
#NLP
models are not designed to handle code-mixing, where each sentence contains multiple languages? Learn how
@samsontmr
@SFResearch
is changing that.
Blog:
Paper:
Code:
So excited to be at
@emnlp2019
this week in Hong Kong, with 7 papers accepted.
Check out our booth with the amazing
@SalesforceEdu
team that, and stay tuned throughout the week for updates on all of our different sessions!
Thank you to everyone who submitted a proposal to our third annual Salesforce AI Research Grant. We’re proud to announce our 2020 round of winners. Congratulations!!
@bluevincent
@Diyi_Yang
@mutembesa
@danqi_chen
Read More:
Do you want to launch your career in machine learning research? Our new AI Residency Program can allow you to do just that. Set yourself up for success in applying to PhD programs w/ real-world experience at one of the industry's top AI research programs.
CodeRL advances program synthesis by integrating pretrained language models + deep reinforcement learning. Using unit test feedback in model training and inference + an improved CodeT5 model, it achieves SOTA results on competition-level programming tasks.
Introducing XGen-Image-1, our first foray into training large text-to-image models. Trained for $75K using TPUs on the LAION dataset, XGen-Image-1 matches the performance of Stable Diffusion 1.5/2.1.
Check out Diffusion-DPO🌟 Bridging the gap between StableDiffusion & closed models like Midjourney v5. Our
#TextToImage
model uses human feedback for state-of-the-art alignment, marking a new era in AI creativity!
Code:
Blog:
We're thrilled to announce this year's
@SFResearch
Deep Learning Grant winners
@ChenhaoTan
@gregd_nlp
@pulkitology
Christopher Ré and Hung-yi Lee! 🎉👏 We're excited to work together to advance the state of AI. Read more about the winning proposals:
🌟 Meet
#Moirai
: Revolutionizing time-series forecasting with universal models! Say goodbye to dataset-specific models and hello 👋 to accurate forecasts across domains!
Code:
LOTSA data:
Blog post:
Introducing COVID-19 Search, a new AI-powered search tool that equips scientists and researchers with the most relevant information about COVID-19.
Learn more about this tool at
We introduce the Salesforce CausalAI Library, an open source library for causal analysis of time series and tabular data.
GitHub:
GitHub Documentation:
Tech Report:
Blog:
Marking our long-awaited return to Twitter with some big news; we're expanding to Singapore 🇸🇬! Excited to partner w/universities across the country in shaping the future of
#AI
,
#NLP
,
#ML
and beyond.
Using both natural and artificial abilities, the human relationship with tools has drastically evolved. The best tools are powerful because they’re easy to use. This is where our skill of language and AI meet.
Learn more on how conversation can power AI >
Editing an image using AI but want to keep the details? Check out our work EDICT (🎆CVPR 2023🎆):
Gradio Demo:
Code:
Arxiv:
Authors:
@bram_wallace
@nikhil_ai
Do you want to make your dog look like a golden retriever? Or get a picture of a cat surfing? Researchers at Salesforce recently developed a new editing algorithm called EDICT - here's a thread on the results and details 🧵
Meet CodeT5 - the first code-aware encoder-decoder pre-trained model that achieves SoTA on 14 sub-tasks in CodeXGLUE! Learn how it’s disrupting software development.
Blog:
Paper:
GitHub:
#codeintelligence
Discover CTRLsum, a generic summarization framework that enables users to control the content of the generated summaries along multiple dimensions.
Blog:
Paper:
Code:
#NLP
#summarization
Can
#AI
language models learn from evolution to design proteins? Learn how Salesforce is taking a step towards enabling solutions to cure disease and clean our planet.
Blog:
Paper:
Our blog for Diffusion-DPO is now live!🚀
In this project we brought the benefits of Reinforcement Learning from Human Feedback (RLHF) to text-to-image diffusion models at scale for the first time.
Meet BLIP: Bootstrapping Language-Image Pre-training for unified Vision-Language understanding/generation. New model architecture + Dataset bootstrapping = SoTA results on a wider range of V+L tasks than other models!
Want to build bots better? Try Converse: a new Task-Oriented Dialogue System that simplifies chatbot building while handling complex tasks and conversations.
#NLP
#AI
Code:
Paper:
Blog:
ETSformer is a time-series forecasting model that combines the classical intuition of seasonal-trend decomposition and exponential smoothing with the Transformer framework, introducing novel exponential smoothing and frequency attention mechanisms.
For time series forecasting, deep learning isn’t scalable for streaming data and non-stationary data makes it hard. FSNet learns deep forecasting models on the fly and handles non-stationary data + concept drift. Learn more >
🎉📚 Our team is on fire! 🔥 Excited to announce that we had 11 papers accepted at ACL 2024! 🚀
Huge kudos to our amazing researchers for their dedication, innovation, and relentless pursuit of excellence. 🌟 Keep pushing the boundaries!
#Research
#Innovation
#ACL2024
Do you want to make your dog look like a golden retriever? Or get a picture of a cat surfing? Researchers at Salesforce recently developed a new editing algorithm called EDICT - here's a thread on the results and details 🧵
Meet Merlion, an end-to-end ML library for Time Series applications. Gives engineers+researchers a 1stop solution to rapidly develop models for their time-series needs and test them across multiple time-series datasets.
Blog:
Code:
Our new AI Residency Program aims to foster the next generation of AI researchers. Our program gives candidates real-world experience and makes them more qualified for top PhD programs.
Applications close January 3, 2022:
Do you want to launch your career in ML research? Our 12-month AI Residency Program can allow you to do just that. Set yourself up for success in applying to PhD programs w/ real-world experience at one of the industry's top AI research programs:
Our NLP team got 16 papers (11 long, 2 short, and 3 finds) at
#emnlp2020
, which cover dialogue, summarization, question answering, multilingual, few-shot, NLI, semantic parsing, data augmentation, etc. Congrats to team members and coauthors. More info about papers coming soon!
"Sorry, I didn't get the question." Sound familiar? 😡Announcing Morpheus, an algorithm developed to combat linguistic discrimination in language models.
Learn more in the links below 👇
Blog:
Paper:
Code:
@SFResearch
&
@Mila_Quebec
announce the AI for Global Climate Cooperation working group & competition.
Help the world by building climate change solutions, using AI to design negotiation protocols & climate agreements. Join us!
@AI4ClimateCoop
Learn more
Why is our xLAM-1B micro model such a big (and by big we mean tiny!) deal? It's
#LeanAI
that packs a specialized punch, runs on less, and keeps your data safer. Open-source release incoming—follow us to stay tuned, and dive into the buzz:
🚀 Introducing our latest breakthrough: the SFR-embedding model, a new champion on the MTEB benchmark! 🥇
But why does it excel?🤔 Read here:
Experience the future of AI with SFR-Embedding-Mistral!⭐
Mark your calendars! 📆 We'll be doing a
@Reddit_AMA
about
#AIEconomist
on r/Futurology Friday Aug 7 from 11am-noon PT. Join
@RichardSocher
,
@StephanZheng
,
@baxterkb
& Harvard's David Parkes to discuss how machine learning and the AI Economist can help improve economic equality.
Today on our blog,
@samsontmr
shares his experience as a Salesforce Industrial PhD Program (IPP) Trainee. His story really has it all - strong mentorship, impactful research, and lots of fun! 🤓🥳
Click the link to get a sneak peek into the IPP 👉
Congrats to our very own
@baxterkb
for being named one of
@ixdasf
's 2020 Women of Design! Kathy is our Architect of Ethical AI Practice and is a true champion of developing responsible AI. We're thrilled to celebrate her success! 🎉
For International Women's Day, IxDA-SF celebrates outstanding members of our community - emerging and established women leaders of our field. Please help us celebrate our 2020 Women of Design!
#ixda
#ixdasf
#interactiondesign
#iwd
#womenofdesign
The
#AIEconomist
Moonshot is here! Join our open source project to build an
#AIEconomist
for the real world. Together, let’s improve the world with
#AI
and
#economics
.
Blog:
Website:
Github:
We're excited to be hosting a tech talk tomorrow on Dynamic Exploration & New Directions in Reinforcement Learning led by
@StephanZheng
@alexrtrott
and Sunil Srinivasa! You won't want to miss this. All
@iclr_conf
attendees welcome
#ICLR2020
Register here:
I'm sure you heard the news!🎉 xGen-mm is out now! 🚀 Our latest batch of open-source foundational
#multimodal
LLM models is here.🌟 It's setting the bar as a cutting-edge model among <5B models, shining in both pre-trained and fine-tuned benchmarks.
[This model was previously
📢Introducing
#AuditNLG
– an open-source library that reduces risks in generative AI for language. It aggregates cutting-edge techniques to enhance trust (Factualness, Safety, Constraint) and simplifies the process through ensemble methods.🚀
#generativeAI
1/2: RnG-KBQA (Rank&Generate Approach for QA over Knowledge Bases) answers natural language questions over large-scale KBs, with strong zero-shot + compositional generalization capabilities; sets new SoTA on widely used KBQA benchmarks.
Blog:
Imagine a world where humans and machines had dialogue to write programs and code together - CodeGen from Salesforce allows the continuation of inputs and outputs with learned behavior to account for efficiency. Let’s ask CodeGen to solve the two-sum problem.
(1/3) Meet LAVIS, an open-source DL library for Language-Vision research/applications.
With a unified interface and modular design, LAVIS supports a wide range of tasks, datasets, and state-of-the-art models. Read more >
And another PhD intern writes a publication accepted to
@iclr2019
!
@AkhileshGotmare
goes into detail on:
1. Cosine learning rate decay
2. Learning rate warmup
3. Knowledge distillation
Learn more in this Q&A, and congrats on starting full-time this week!
Meet Merlion, an open-source Python library for time series intelligence. Solve a range of problems with a one-stop solution to rapidly develop models for specific time-series needs, and benchmark them across datasets. Learn more with our demo >
Are you attending
#acl2020nlp
? The main
@aclmeeting
conference started today and our team is presenting some exciting new research! Be sure to check it out:
Introducing the AI Economist, an AI framework for economic policy design. The AI Economist is a new way that reinforcement learning can drive positive, social change. Learn more about this exciting innovation:
Q&A:
Blog:
Excited to introduce the AI Economist: Extends ideas from Reinforcement Learning for tackling inequality through learned tax policy design.
The framework optimizes productivity and equality.
Blog:
Paper:
Q&A:
Everyone say "
#AI
"📸
Day ✌️ of
#ICML2019
is in the books and the best's yet to come! Join us tomorrow in the Pacific Ballroom from 6:30-9pm for our paper preso's ranging from
#machinelearning
to
#reinforcementlearning
.
Learn more on our research at:
1/2 The human effort needed to create bounding-box labels of training data means most AI object detection methods work on limited categories. Our new method automatically generates pseudo bbox labels of diverse objects from large-scale image-caption pairs.
Problem: LLMs excel at code generation, but outputs often contain security blindspots. Fine-tuning alone can't keep pace with sophisticated attacks.
Solution: Enter INDICT - our new framework that empowers LLMs with Internal Dialogues of Critiques, boosting code safety by >80%
"Addressing catastrophic forgetting is one of the key challenges in continual learning where machine learning systems are trained with sequential or streaming tasks."
Hear about our framework at 5:10pm!
#ICML19
Chatbots are often frustrating to use - and to make. Converse, the better bot-builder is a flexible modular task-oriented dialogue system that lets developers easily create smart chatbots to help users complete complex tasks.
#NLP
#AI
Check out our demo:
Salesforce AI researchers have developed a new data-driven framework to improve the diversity and explainability of enterprise app recommendation systems. Learn more:
ICYMI: Our multimodal dataset MINT1T has 1 trillion text tokens and 3 billion images! 🌟 It's 10x larger than the biggest existing open source dataset. Check it out:
Technical report:
Github:
#Multimodal
#AI
It's the time we've all been waiting for,
@iclr2019
!!
We've got 6 publications accepted from our researchers, an amazing booth run by our
@SalesforceEdu
team, and even more.
Click the link below to check out our footprint, and tune this week for updates!
Reminder that our 2020 Salesforce AI Research Grant application deadline is in two weeks on Oct 16, 2020! We've already received some amazing submissions! Keep them coming! 📢📢
Website:
Blog:
@CaimingXiong
Woot woot! Our paper on training a system on sequences of explanations for commonsense reasoning and highlighted annotations was accepted to
@ACL2019_Italy
!
Catch us there on Mon, 7/29, and see this great article from
@venturebeat
It was just last week that we were at
@iclr2019
, showcasing the 6 publications that our stellar research team had accepted.
Check out the highlights of the event below, including some team fun!
(1/2) Our new AI Residency program is currently accepting applications! This 12-month research training program is intended to kickstart or further your experience in
#AI
research.
When it comes to CRM use cases, LLMs are not “one size fits all.” Announcing the world’s first LLM benchmark for CRM, allowing you to select the right model for the right task, across four key dimensions: Accuracy, Cost Speed, and Trust & Safety. Read the press release and
Can neural networks use auto-generated reasoning?
Today, at
@ACL2019_Italy
, we had a session on leveraging language models for commonsense reasoning from our very own
@nazneenrajani
!
Check out the paper below:
We present BotSIM, a data-efficient end-to-end Bot SIMulation toolkit for evaluation, diagnosis, and improvement of commercial task-oriented dialogue (TOD) systems. Read more on our framework >
As text generation models become more creative, evaluating progress becomes more challenging. Near-Negative Distinction is a new evaluation method bridging human and automatic evaluation by re-purposing previous human evaluation annotations. Learn more >
(1/2): Meet OmniXAI: comprehensive one-stop ML library; makes Explainable AI easy for data scientists, ML researchers, or engineers to analyze, debug, and interpret ML models for various data types at different stages of the ML process.
Blog: