#php#calendar#contacts#crm#crm_platform#crm_system#customer_portal#customer_support#customizable#documents#email_marketing#kanban#leads#open_source#php#platform#sales_automation#single_page_application#support
EspoCRM is a free, open-source CRM tool that helps you manage customer relationships by organizing leads, contacts, sales, marketing, and support in one easy-to-use web app. It has a clean interface, customizable features, and a REST API for integration, making it flexible for startups, small businesses, and developers. It automates repetitive tasks, saving time and reducing errors, while providing detailed reports to improve decision-making. Being open-source, it’s cost-effective with no licensing fees, and supported by a helpful community. This means you get a powerful, adaptable CRM that boosts productivity and customer management without high costs[1][3][5].
https://github.com/espocrm/espocrm
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What’s Really Going On in Machine Learning? Some Minimal Models—Stephen Wolfram Writings
https://writings.stephenwolfram.com/2024/08/whats-really-going-on-in-machine-learning-some-minimal-models/
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Meta's second version of segment anything.
https://github.com/facebookresearch/segment-anything-2
They have a nice demo:
https://sam2.metademolab.com/
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I was searching for a tool to visualize computational graphs and ran into this preprint. The hierarchical visualization idea is quite nice.
https://arxiv.org/abs/2212.10774
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Like a dictionary
Kunc, Vladim’ir, and Jivr’i Kl’ema. 2024. “Three Decades of Activations: A Comprehensive Survey of 400 Activation Functions for Neural Networks.” arXiv [Cs.LG], February. http://arxiv.org/abs/2402.09092.
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I got interested in satellite data last year and played with it a bit. It's fantastic. The spatiotemporal nature of it brings up a lot of interesting questions.
Then I saw this paper today:
Rolf, Esther, Konstantin Klemmer, Caleb Robinson, and Hannah Kerner. 2024. “Mission Critical -- Satellite Data Is a Distinct Modality in Machine Learning.” arXiv [Cs.LG], February. http://arxiv.org/abs/2402.01444.
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Jelassi S, Brandfonbrener D, Kakade SM, Malach E. Repeat after me: Transformers are better than state space models at copying. arXiv [cs.LG]. 2024. Available: http://arxiv.org/abs/2402.01032
Not surprising at all when you have direct access to a long context. But hey, look at this title.