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    Automatic robot perception programming by imitation learning
    1.
    发明授权
    Automatic robot perception programming by imitation learning 有权

    公开(公告)号：US11577388B2

    公开(公告)日：2023-02-14

    申请号：US16455190

    申请日：2019-06-27

    申请人： Intel Corporation

    发明人： David I. Gonzalez Aguirre ,  Javier Felip Leon ,  Javier Sebastián Turek ,  Luis Carlos Maria Remis ,  Ignacio Javier Alvarez ,  Justin Gottschlich

    IPC分类号： B25J9/16

    摘要： Apparatus, systems, methods, and articles of manufacture for automatic robot perception programming by imitation learning are disclosed. An example apparatus includes a percept mapper to identify a first percept and a second percept from data gathered from a demonstration of a task and an entropy encoder to calculate a first saliency of the first percept and a second saliency of the second percept. The example apparatus also includes a trajectory mapper to map a trajectory based on the first percept and the second percept, the first percept skewed based on the first saliency, the second percept skewed based on the second saliency. In addition, the example apparatus includes a probabilistic encoder to determine a plurality of variations of the trajectory and create a collection of trajectories including the trajectory and the variations of the trajectory. The example apparatus also includes an assemble network to imitate an action based on a first simulated signal from a first neural network of a first modality and a second simulated signal from a second neural network of a second modality, the action representative of a perceptual skill.

    METHODS AND APPARATUS TO TRAIN MODELS FOR PROGRAM SYNTHESIS
    5.
    发明申请
    METHODS AND APPARATUS TO TRAIN MODELS FOR PROGRAM SYNTHESIS 有权

    公开(公告)号：US20220108182A1

    公开(公告)日：2022-04-07

    申请号：US17551170

    申请日：2021-12-14

    申请人： Intel Corporation

    发明人： Todd A. Anderson ,  Shengtian Zhou ,  Javier Turek ,  Celine Lee ,  Justin Gottschlich

    IPC分类号： G06N3/08 ,  G06F40/30 ,  G06N3/04

    摘要： Methods and apparatus to train models for program synthesis are disclosed. A disclosed example apparatus includes at least one memory, instructions, and processor circuitry. The processor circuitry is to execute the instructions to sample pairs of programs, the pairs of programs including first programs and second programs, the first programs including natural language descriptions and second programs, calculate program similarity scores corresponding to the pairs of programs, and train a model based on entries corresponding to ones of the pairs of programs, at least one of the entries including a corresponding one of the natural language descriptions with a paired one of the second programs, and a corresponding one of the program similarity scores.

    TUNING OF LOOP ORDERS IN BLOCKED DENSE BASIC LINEAR ALGEBRA SUBROUTINES
    9.
    发明申请
    TUNING OF LOOP ORDERS IN BLOCKED DENSE BASIC LINEAR ALGEBRA SUBROUTINES 审中-公开

    公开(公告)号：US20190318225A1

    公开(公告)日：2019-10-17

    申请号：US16454318

    申请日：2019-06-27

    申请人： Intel Corporation

    发明人： Alexander Heinecke ,  Evangelos Georganas ,  Justin Gottschlich

    IPC分类号： G06N3/04 ,  G06N3/08 ,  G06F9/30

    摘要： An example includes a sequence generator to generate a plurality of sequence pairs, a first one of the sequence pairs including: (i) a first input sequence representing first accesses to first tensors in a first loop nest of a first computer program, and (ii) a first output sequence representing a first tuned loop nest corresponding to the first accesses to the first tensors in the first loop nest; a model trainer to train a recurrent neural network based on the sequence pairs as training data, the recurrent neural network to be trained to tune loop ordering of a second computer program based on a second input sequence representing second accesses to a second tensor in a second loop nest of the second computer program; and a memory interface to store, in memory, a trained model corresponding to the recurrent neural network.

    METHODS AND APPARATUS TO OPTIMIZE WORKFLOWS
    10.
    发明申请
    METHODS AND APPARATUS TO OPTIMIZE WORKFLOWS 审中-公开

    公开(公告)号：US20190317805A1

    公开(公告)日：2019-10-17

    申请号：US16451974

    申请日：2019-06-25

    申请人： Intel Corporation

    发明人： Thijs Metsch ,  Joseph Butler ,  Mohammad Mejbah Ul Alam ,  Justin Gottschlich

    IPC分类号： G06F9/48 ,  G06N20/00

    摘要： Methods, apparatus, systems and articles of manufacture are disclosed that optimize workflows. An example apparatus includes an intent determiner to determine an objective of a user input, the objective indicating a task to be executed in an infrastructure, a configuration composer to compose a plurality of workflows based on the determined objective, a model executor to execute a machine learning model to create a confidence score relating to the plurality of workflows, and a workflow selector to select at least one of the plurality of workflows for execution in the infrastructure, the selection of the at least one of the plurality of workflows based on the confidence score.