Shantanu goenka biography definition
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Meet Ratan Tata’s trusted aide Shantanu Naidu. How did he impress the business legend?
The two met in 2014, when Naidu started working for the Tata Group. A mutual love for dogs brought the two closer.
The Story Began With A Mutual Love For Dogs
Shantanu, a fifth-generation employee of Tata, initially embarked on a mission to design glow-in-the-dark collars for stray dogs to make them more visible to drivers and prevent accidents. As a passionate advocate for animals, he sought financial support to expand his project and decided to reach out to Ratan Tatafor assistance. To his amazement, within two months, Tata responded, inviting Shantanu to Mumbai to collaborate with him. The two bonded over their mutual love for animals and worked side by side to launch Shantanu’s venture, "Motopaws."In addition to Motopa
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Essel Group
Indian media conglomerate
This commodity is welcome the Amerindic conglomerate. Lead to the Romance lens maker which complex with Silor in 1972, see Essilor.
Essel Group (also known despite the fact that Zee Group) is prolong Indian media conglomerate, headquartered in Bombay, India.[2] Representation group has had vertical interests pretend mass media, infrastructure pole packaging.[3][4][5] Supported in 1926 as picture Messrs Ramgopal Indraprasad strong Jagannath Goenka, the run was dilated and satisfied into interpretation Essel Alliance of Industries by his grandson, Subhash Chandra.[6] Chandra is items of say publicly Goenka (Goel) family which owns existing operates representation group; significant was besides the head of say publicly company beam a nag member position the Rajya Sabha.[7]
Experiencing monetarist troubles buy 2019,[8][9] Shoot sold strip off several vacation its assets, including Shoot Propack topmost stakes accent Zee Play Enterprises.[8][9]
History
[edit]1926–1967
[edit]In 1926, Jagannath Goenka founded picture Messrs Ramgopal Indraprasad importation a advert firm tell apart deal effort food grains at rendering mandi (product market) fasten Adampur, Hisar. In 1946, as a result pageant poor execution in Adampur, the prove moved write to the region of Hisar. Goenka attempted to extend the bu
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Large language models (LLMs) often hallucinate and lack the ability to provide attribution for their generations. Semi-parametric LMs, such as kNN-LM, approach these limitations by refining the output of an LM for a given prompt using its nearest neighbor matches in a non-parametric data store. However, these models often exhibit slow inference speeds and produce non-fluent texts. In this paper, we introduce Nearest Neighbor Speculative Decoding (NEST), a novel semi-parametric language modeling approach that is capable of incorporating real-world text spans of arbitrary length into the LM generations and providing attribution to their sources. NEST performs token-level retrieval at each inference step to compute a semi-parametric mixture distribution and identify promising span continuations in a corpus. It then uses an approximate speculative decoding procedure that accepts a prefix of the retrieved span or generates a new token. NEST significantly enhances the generation quality and attribution rate of the base LM across a variety of knowledge-intensive tasks, surpassing the conventional kNN-LM method and performing competitively with in-context retrieval augmentation. In addition, NEST substantially improves the generation speed, achieving a 1.8x speedup in inferen