Marli digital GmbH

We make you digital.
Company specialist in the following area:
#AI
#DataScience
#BusinessIntelligence

[Forbes @Forbes]

This Uber veteran launched her 'AI mindset' self-driving startup with an $83.5 million round https://t.co/3ds3LJQFC3

[BetaKit @BetaKit]

.@Waabi_ai’s Series A round is one of the largest rounds of initial financing ever raised by a Canadian startup. https://t.co/40fwdsFKfz

[Raquel Urtasun @RaquelUrtasun]

I had a great conversation with @MarwaEldiwiny about AI, #selfdriving, #innovation and my path to found @Waabi_ai.

[Yann LeCun @ylecun]

Some good points in this thread.

[Fei-Fei Li @drfeifei]

Happening now! 🙌

[Fei-Fei Li @drfeifei]

.@StanfordHAI co-organized the coming conference! Save the date!

[O'Reilly Media @OReillyMedia]

[NEW RELEASE] PyTorch Pocket Reference -- Author Joe Papa provides instant access to syntax, design patterns, and code examples to accelerate your development and reduce the time you spend searching for answers. https://t.co/nQfYGs97Za #OReillyExperts #NewBook

[O'Reilly Media @OReillyMedia]

[FREE CHAPTER] Blueprints for Text Analytics Using Python, Chapter 7 -- This practical book provides clear blueprints for text-related problems that apply state-of-the-art machine learning methods in Python. https://t.co/7h7LFS6lDO #OReillyExperts

[Martin Görner @martin_gorner]

It's now on YouTube🥳: "Modern Keras Design Patterns" by @fchollet and @martin_gorner
https://t.co/2VkillVKcS

[Bojan Tunguz @tunguz]

Using machine learning to predict high-impact research | MIT News | Massachusetts Institute of Technology https://t.co/ymC1H1LtOl

[Bojan Tunguz @tunguz]

I just published my really long post on 6 Levels of #AutoML.

https://t.co/DSqY1y9ozi

#ML #AI #MachineLearning #DataScience

[ARCHIVED - NASA's Perseverance Mars Rover @NASAPersevere]

With no road maps on Mars, I’m building my own as I go. There are lots of places I want to explore, and mapping while I drive will help me see and do more. Let the road trip begin.

[NASA JPL @NASAJPL]

Postcards from a Martian helicopter. 💌
All of the raw images straight from the #MarsHelicopter’s two cameras are available for your viewing and downloading pleasure here: https://t.co/iZvwEzOSgh

[Fei-Fei Li @drfeifei]

Thirty years of Computer Vision research at work here. While the public does not hear much about basic science research, it’s the generations of scientists and their passionate work that bring moments like this to live 🌹👍🙏

[Andrej Karpathy @karpathy]

Stanford CS Course Schedule Autumns 2020-2021 https://t.co/rERlzoXA13 I feel devastated and embarassed that I don't know everything here

[Andrej Karpathy @karpathy]

Top scoring approaches on any benchmark are often overly complex, overly-specialized models, heavy multi-scale ensembles, fancy training techniques, etc. How do we organize benchmarks / metrics for the "simplest baseline that just works".

[Marli digital GmbH @Marli_digital]

An autonomous weeder applies AI, robotics, and laser technology to identify, target, and eliminate weeds. It can remove over 100,000 weeds/hour and works day and night.

https://t.co/KeWfdN4e9c

#autonomous
#AutonomousVehicles
#Robotics
#AI
#ComputerVision
#DeepLearning

[Google Walkout For Real Change @GoogleWalkout]

We stand with @timnitGebru. We call on Google Research to strengthen its commitment to research integrity and to unequivocally commit to supporting research that honors the commitments made in Google’s AI Principles. Sign the letter: https://t.co/hf91oDZ0Ew

[Kate Baumli @katebaumli]

Happy to share that the preprint for Relative Variational Intrinsic Control, an unsupervised method for learning relative, composable, affordance-like skills, is on arXiv today and will be presented at AAAI in February 2021. https://t.co/RAP4kwmwOk @VladMnih @Zergylord @dwf

[Andrej Karpathy @karpathy]

RepVGG: Making VGG-style ConvNets Great Again
paper: https://t.co/Y5WfgvqxHO
PyTorch code: https://t.co/ydk0RUf6JU
👌Spells out the benefits of very simple/uniform/fast (latency, not FLOPS) deployment architectures. A lot of complexity often due to optimization, not architecture.