Discover and read the best of Twitter Threads about #artificialintelligence

Most recents (24)

1/ @huggingface: The #ArtificialIntelligence community building the future

Behind the hugging face emoji 🤗 is the fastest growing open source community in history

If you have not heard of @huggingface, it may be one of most important platforms of the next decade
2/ Founders @ClementDelangue , @Thom_Wolf, and @julien_c originally set out to build open domain AI.

Quickly, they realized the technology and platform they were building was bringing value to companies.

They decided to open source it
3/ Two and a half years later, the platform has exploded to over 10,000 models, 1,000 datasets, and 45,000 GitHub stars

Read 23 tweets
Daily Bookmarks to GAVNet 06/09/2021…
China’s Hot Summer Is Latest Test of Its Carbon-Neutrality Drive…

#china #ClimateChange #CarbonNeutrality #consequences
Quantum Computing and Reinforcement Learning Are Joining Forces to Make Faster AI…

#QuantumComputing #ReinforcementLearning #ArtificialIntelligence
Read 10 tweets
𝗧𝘆𝗽𝗲𝘀 𝗼𝗳 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴: 𝗥𝗲𝗶𝗻𝗳𝗼𝗿𝗰𝗲𝗺𝗲𝗻𝘁 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴

In the reinforcement learning paradigm, the learning process is a loop in which the agent reads the state of the environment and then executes an action.
Then the environment returns its new state and a reward signal, indicating if the action was correct or not. The process continues until the environment reaches a terminal state or if a maximum number of iterations is executed.
These are some of the main concepts in Reinforcement Learning:
Read 10 tweets
Daily Bookmarks to GAVNet 05/29/2021…
Variants of concern are overrepresented among post-vaccination breakthrough infections of SARS-CoV-2 in Washington State…

#VariantsOfConcern #PostVaccination #BreakthroughInfections #COVID19 #WashingtonState
Read 10 tweets
Russia’s Role in the US Elections: The Case for Caution
December 16, 2016

by George Beebe, former CIA Director of Russia Analysis AND former President of BehaviorMatrix AND current V.P. at 'Center for the National Interest' under 'Dimitri Simes, President…
George Beebe

George Beebe is (was) the president of BehaviorMatrix LLC, a text analytics company, and formerly served as chief of Russia analysis at the CIA. Image

Dimitri Simes is PRESIDENT of 'Center for the National Interest'.

George Beebe is now VICE PRESIDENT of 'Center for the National Interest'.

BehaviorMatrix, LLC did POLITICAL CAMPAIGN INFLUENCING as early as 2013 or earlier.

Read 69 tweets
Divide and Contrast: Self-supervised Learning from Uncurated Data

🔎📚 Paper:
👨‍🎓 👩🏾‍🎓 Credit: Yonglong Tian, Olivier J. Henaff, Aaron van den Oord

#technology #data #machinelearning #ml #artificialintelligence #ai #computervision #cv #PatternRecognition
#Selfsupervised learning holds promise in leveraging large amounts of unlabeled data, however much of its progress has thus far been limited to highly curated pre-training data such as #ImageNet.
They explore the effects of contrastive learning from larger, less-curated image datasets such as YFCC, and find there is indeed a large difference in the resulting representation quality.
Read 6 tweets
Daily Bookmarks to GAVNet 05/17/2021…
Battlestar Galactica Lessons from Ransomware to the Pandemic…

#ransomware #PandemicResponse #LessonsLearned
Female northern elephant seals spend 18 hours a day foraging in deep sea…

#FemaleSeals #foraging #BehaviorTracking
Read 10 tweets
Identification and Avoidance
of Static and Dynamic Obstacles
on PointCloud for UAVs Navigation

🔎📚 Paper:
👨‍🎓 👩🏾‍🎓 Credit: Han Chen and Peng Lu

#technology #data #machinelearning #ml #artificialintelligence #ai #robotics #robots #3D #autonomous #uavs
Avoiding hybrid obstacles in unknown scenarios with an efficient flight strategy is a key challenge for unmanned aerial vehicle applications.
In this paper, they introduce a technique to distinguish dynamic obstacles from static ones with only point cloud input.

Then, a computationally efficient obstacle avoidance motion planning approach is proposed and it is in line with an improved relative velocity method.
Read 6 tweets
This paper presents an AI system applied to location and robotic grasping.

👨‍🎓 👩🏾‍🎓 Credit: Víctor de Gea Rodríguez, Santiago T. Puente, Pablo Gil
Experimental setup is based on a parameter study to train a deep-learning network based on Mask-RCNN to perform waste location in indoor and outdoor environment, using five different classes and generating a new waste dataset.
Read 5 tweets
Towards Sensor Data Abstraction
of Autonomous Vehicle Perception Systems

🔎📚 Paper:

#technology #data #science #machinelearning #ml #artificialintelligence #ai #computervision #cv #PatternRecognition #3D #autonomous #camera #lidar #radar ImageImageImage
👨‍🎓 👩🏾‍🎓 Credit: Hannes Reichert, Lukas Lang, Kevin Rösch, Daniel Bogdoll, Konrad Doll, Bernhard Sick, Hans-Christian Reuss, Christoph Stiller, J. Marius Zöllner
Full-stack autonomous driving perception modules usually consist of data-driven models based on multiple sensor modalities.
Read 7 tweets
Not All Memories are Created Equal: Learning to Forget by Expiring

🔎📚 Paper:

#tech #machinelearning #ml #artificialintelligence #fb #facebook Image
👨‍🎓 👩🏾‍🎓 Credit: Sainbayar Sukhbaatar, Da Ju, Spencer Poff, Stephen Roller, Arthur Szlam, Jason Weston, Angela Fan
Attention mechanisms have shown promising results in sequence modeling tasks that require longterm memory.

However, not all content in the past is equally important to remember.
Read 8 tweets
There are three concepts that are at the core of machine learning:
data, a model, and learning.

Machine learning is about designing algorithms that automatically extract valuable information from data.

#ml #machinelearning #ai #artificialintelligence #Maths #Mathematics Image
The emphasis here is on “automatic”, i.e., ml is concerned about general-purpose methodologies that can be applied to many datasets, while producing something that is meaningful.
Since machine learning is inherently data driven, data is at the core data
of machine learning.

The goal of machine learning is to design general-purpose methodologies to extract valuable patterns from data, ideally without much domain-specific expertise.
Read 8 tweets
To LiDAR or not to LiDAR - Thoughts? 🧠
LIDAR vs. Camera —
Which Is The Best for Self-Driving Cars?


#technology #data #science #machinelearning #ml #artificialintelligence #ai #3D #autonomous #tesla #waymo #selfdrivingcars #lidar
Breakthrough #Lidar Technology
Gives @argoai the Edge
in Autonomous Delivery and Ride-Hail Services
With the introduction of Argo Lidar, the global self-driving technology company Argo AI has overcome the limitations preventing most competitors from commercializing autonomous delivery and ride-hail services.
Read 5 tweets
Neuroscience-inspired perception-action in robotics:
applying active inference for state estimation,
control and self-perception

🔎📚 Paper:
👨‍🎓 👩🏾‍🎓 Credit: Pablo Lanillos, Marcel van Gerven
Unlike robots, humans learn, adapt and perceive their bodies by interacting with the world.
Discovering how the brain represents the body and generates actions is of major importance for robotics and artificial intelligence.
Read 8 tweets
Design principles for
a hybrid intelligence decision support system
for business model validation

🔎📚 Paper:

#technology #data #machinelearning #ml #artificialintelligence #ai #startups #businessmodels #tensorflow #SQL #entrepreneurs
👨‍🎓 👩🏾‍🎓 Credit: Dominik Dellermann, Nikolaus Lipusch, Philipp Ebel, Jan Marco Leimeister
One of the most critical tasks for startups is to validate their business model.

Therefore, entrepreneurs try to collect information such as feedback from other actors to assess the validity of their assumptions and make decisions.
Read 5 tweets
Hierarchical Graph Neural Networks

🔎📚 Paper:
👨‍🎓 👩🏾‍🎓 Credit: Stanislav Sobolevsky

#technology #data #machinelearning #ml #artificialintelligence #ai #GNN #CNN #NN #neuralnetworks #graphicneuralnetworks #deeplearning
Over the recent years, Graph Neural Networks have become increasingly popular in network analytic and beyond.

With that, their architecture noticeable diverges from the classical multi-layered hierarchical organization of the traditional neural networks.
At the same time, many conventional approaches in network science efficiently utilize the hierarchical approaches to account for the hierarchical organization of the networks, and recent works emphasize their critical importance.
Read 8 tweets
Jerk Control of Floating Base Systems with
Contact-Stable Parametrised Force Feedback

🔎📚 Paper:

#technology #data #science #machinelearning #ml #artificialintelligence #ai #robotics #robots #computervision #cv #PatternRecognition #humanoidrobot
👨‍🎓 👩🏾‍🎓 Credit: Ahmad Gazar, Gabriele Nava, Francisco Javier Andrade Chavez, Daniele Pucci
Nonlinear controllers for floating base systems incontact with the environment are often framed as quadratic programming #QP optimization problems.
Read 6 tweets
Deep dive into "ZeRO: Memory Optimizations Toward Training Trillion Parameter Models" by Samyam Rajbhandari, Olatunji Ruwase, Yuxiong He & @jeffra45

It proposes an optimizer to build huge language pre-trained models.

Thread👇🏼 🔎…
Zero Redundancy Optimizer (ZeRO) is an optimization module that maximizes both memory and scaling efficiency.

It tries to address the limitations of data parallelism and model parallelism while achieving the merits of both…

Read 7 tweets
Daily Bookmarks to GAVNet 05/06/2021…
Prior SARS-CoV-2 infection rescues B and T cell responses to variants after first vaccine dose…

#COVID19 #variants #vaccines #immunity
Book Review: The Next Frontier of Warfare Is Online…

#cyberattacks #malware #hacking #DigitalMarkets #StateSctors
Read 10 tweets

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