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The DARPA PAL program (the Personalized Assistant that Learns) focused on improving the way that computers support humans through the use of cognitive systems-that is, systems that reason, learn from experience, and accept guidance in order to provide effective, personalized assistance. SRI International has led the PAL Framework effort to make available many of the successful machine learning and reasoning technologies developed on the PAL program for use by the broader DARPA, research, and military communities. Technical capabilities within the framework have been hardened, modularized, packaged, and where appropriate, adapted to meet industry standards to facilitate their incorporation into potential target applications. The framework further includes various infrastructure components and APIs to simplify integration with the framework technologies.

"Torch is a scientific computing framework with wide support for machine learning algorithms. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation."

The Allen Institute for Artificial Intelligence supports individual researchers and research groups. We also sponsor conferences, prizes, competitions, and the construction of large public knowledge bases and evaluation frameworks. We are particularly interested in partnering with corporate and public-sector entities in order to leverage complementary resources.

Here at OpenCog, we're creating an open source Artificial General Intelligence framework, intended to one day express general intelligence at the human level and beyond.

"Build and connect intelligent bots to interact with your users naturally wherever they are, from text/sms to Skype, Slack, Office 365 mail and other popular services."

"An open source machine learning framework that accelerates the path from research prototyping to production deployment."

"A unified platform for training and evaluating dialog models across many tasks. Multitask training over many datasets at once. Supports dialog models in PyTorch, Tensorflow, Theano, Torch, and other frameworks. Seamless integration of Amazon Mechanical Turk for data collection, training and human evaluation."

"People + AI Research (PAIR) is a multidisciplinary team at Google that explores the human side of AI by doing fundamental research, building tools, creating design frameworks, and working with diverse communities."

"TensorFlow Quantum is a library for hybrid quantum-classical machine learning. # A hybrid quantum-classical model. model = tf.keras.Sequential([     # Quantum circuit data comes in inside of tensors.     tf.keras.Input(shape=(), dtype=tf.dtypes.string),     # Parametrized Quantum Circuit (PQC) provides output     # data from the input circuits run on a quantum computer.   TensorFlow Quantum (TFQ) is a quantum machine learning library for rapid prototyping of hybrid quantum-classical ML models. Research in quantum algorithms and applications can leverage Google's quantum computing frameworks, all from within TensorFlow."