View source for 18237887. LSTM CIRCUIT WITH SELECTIVE INPUT COMPUTATION simplified abstract (Intel Corporation)

=LSTM CIRCUIT WITH SELECTIVE INPUT COMPUTATION=


==Organization Name==

[[:Category:Intel Corporation|Intel Corporation]]


[[Category:Intel Corporation]]

==Inventor(s)==

[[:Category:Ram Krishnamurthy of Portland OR (US)|Ram Krishnamurthy of Portland OR (US)]][[Category:Ram Krishnamurthy of Portland OR (US)]]

[[:Category:Gregory K. Chen of Portland OR (US)|Gregory K. Chen of Portland OR (US)]][[Category:Gregory K. Chen of Portland OR (US)]]

[[:Category:Raghavan Kumar of Hillsboro OR (US)|Raghavan Kumar of Hillsboro OR (US)]][[Category:Raghavan Kumar of Hillsboro OR (US)]]

[[:Category:Phil Knag of Hillsboro OR (US)|Phil Knag of Hillsboro OR (US)]][[Category:Phil Knag of Hillsboro OR (US)]]

[[:Category:Huseyin Ekin Sumbul of Portland OR (US)|Huseyin Ekin Sumbul of Portland OR (US)]][[Category:Huseyin Ekin Sumbul of Portland OR (US)]]

==LSTM CIRCUIT WITH SELECTIVE INPUT COMPUTATION - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18237887 titled 'LSTM CIRCUIT WITH SELECTIVE INPUT COMPUTATION

==Simplified Explanation==

The patent application describes an apparatus that includes a long short term memory (LSTM) circuit with a multiply accumulate circuit (MAC). The MAC circuit has a feature that allows it to use a stored product term instead of performing a multiplication operation, if the accumulation of differences between consecutive input values has not reached a certain threshold.

* The apparatus includes a long short term memory (LSTM) circuit with a multiply accumulate circuit (MAC).
* The MAC circuit has circuitry that can use a stored product term instead of performing a multiplication operation.
* This feature is utilized when the accumulation of differences between consecutive input values has not reached a threshold.
* The stored product term is relied upon to determine the product term in such cases.
* The apparatus provides a more efficient way of handling calculations in the LSTM circuit.

== Potential Applications ==
* Artificial intelligence and machine learning systems
* Natural language processing and speech recognition systems
* Robotics and autonomous systems
* Financial analysis and prediction models

== Problems Solved ==
* Reduces the computational load on the LSTM circuit by avoiding unnecessary multiplication operations.
* Improves the efficiency and speed of calculations in the LSTM circuit.
* Helps to optimize the performance of AI and machine learning systems.

== Benefits ==
* Faster and more efficient processing of data in LSTM circuits.
* Reduced power consumption and improved energy efficiency.
* Enhanced performance and accuracy of AI and machine learning models.
* Cost savings in terms of hardware requirements for AI systems.


==Original Abstract Submitted==

An apparatus is described. The apparatus includes a long short term memory (LSTM) circuit having a multiply accumulate circuit (MAC). The MAC circuit has circuitry to rely on a stored product term rather than explicitly perform a multiplication operation to determine the product term if an accumulation of differences between consecutive, preceding input values has not reached a threshold.



[[Category:G06N3/063]]
[[Category:G06F7/523]]
[[Category:G06F9/38]]
[[Category:G06F9/30]]
[[Category:G06F7/509]]
[[Category:G06F7/544]]