The project, which is at a very initial stage right now, is looking to harness the vast internal code, data and resources that the country’s largest software services firm has. The solution will be built through in-house algorithms that use large language modelling functions similar to generative artificial intelligence<\/a> (AI) chatbots such as ChatGPT but for enterprise code generation.
“The way we look at it, it (generative AI) uses past code, data and experience to learn,” Subramaniam told ET. “And over the many years that TCS<\/a> has been in business, I can use all of my knowledge as a base. So, if that technology uses and generates code that I have taught the algorithm using TCS proprietary data, then the outcome is something that I am willing to license.”
He said TCS is working on use cases to build proprietary generative AI algorithms to build code and the process has to mature further. He believes enterprise usage of these generative AI solutions still requires finetuning in terms of ownership and IP of the end products, hence enterprise solutions will see demand.
Subramaniam, who retires in May next year, expects the Mumbai-based software firm to roll out some of these solutions before the end of his tenure. “The focus is really to build models and using those models, generate the code that can be deployed,” he said.
He said if TCS wants to provide secure and contextual generative AI solutions to accelerate client projects, it cannot depend only on multiple large language tools from different providers but should have its own solution.
“Everybody (clients) is ready to use generative AI. But then, as a supplier, I am obliged to deliver them something which is free of any infringement, and full ownership of the intellectual property,” Subramaniam said.
Also, the industry will have to wait for regulations governing these solutions to mature further to realise the full potential of the technology, he said.
Prompt Engineers<\/strong>
Subramaniam sees a huge opportunity in creating new roles for “prompt engineers” within the organisation who can effectively communicate contextual queries to large language models for enterprise requirements.
“So, one of the things that we are hearing in the market is that the way you prompt the questions to generative AI platforms is very important, right? So, we are conceptualising a role called ‘prompt engineers’ within the organisation,” he said. “We are yet to get approval on it, but we know that this role will be as critical as having engineering, mathematical or analytical skills.”
TCS sees an opportunity to integrate its generative AI offering with its low-code software development platform MasterCraft.
This will be similar to Copilot – a solution to auto-generate code, launched by Microsoft-owned GitHub<\/a> and OpenAI<\/a> in October 2021, to help write software programs faster.
“As of today, over 100 clients are using the Mastercraft tool,” Subramaniam said. “We have not put ChatGPT-like solutions for data pattern intelligence into it. But when we do eventually, our vision for MasterCraft to be a (intelligent) low-code platform will come true.”
He said TCS has already built a number of internal use cases using generative AI solutions while also working with global partners.
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读到
塔塔咨询服务公司(TCS)是建造自己的ChatGPT相当于用于企业代码生成,其首席运营官N Ganapathy苏说。
在非常初期的项目,现在正在寻求利用巨大的内部代码,数据和资源,中国最大的软件服务公司。解决方案将通过内部构建算法,使用大型语言造型类似于生殖功能人工智能(AI)聊天机器人如ChatGPT但企业代码生成。
“我们看它的方式,它(生成AI)使用过去的代码,数据和经验学习,”苏告诉ET。”和许多年TCS已经在商业领域,我可以用我所有的知识作为基础。所以,如果技术使用和生成代码,我教使用TCS专有数据的算法,然后结果是我愿意许可。”
他说,TCS正在用例构建专有生成人工智能算法来构建代码和过程进一步成熟。他认为企业使用这些生成人工智能解决方案仍然需要整合的所有权和知识产权的产品,因此企业解决方案将会看到需求。
苏,明年5月退休,预计孟买软件公司推出的这些解决方案在任期即将结束时。“重点是构建模型和使用这些模型,生成的代码可以部署,”他说。
他说如果TCS想提供安全上下文生成人工智能解决方案加速客户项目,它不能只取决于多个大型语言工具从不同的提供者,但应该有自己的解决方案。
“每个人(客户)可以使用生成的人工智能。但是,作为一个供应商,我必须提供他们一些免费的任何侵权行为,和完整的知识产权的所有权,”苏说。
同时,该行业将不得不等待规定这些解决方案成熟进一步意识到技术的潜力,他说。
促使工程师
Subramaniam看到一个巨大的机会,在创建新角色组织内的“促使工程师”谁能有效沟通上下文查询大型语言模型为企业需求。
”的一件事,我们在市场上听到这就是你提示的问题生成人工智能平台是非常重要的,对吧?所以,我们即可形成一个角色被称为“促使工程师”组织内部,”他说。“我们尚未得到批准,但我们知道这个角色将作为重要的工程,数学或分析能力。”
TCS看到了一个机会将其生成AI提供与其low-code MasterCraft软件开发平台。
这将是类似于副驾驶——解决方案自动生成代码,由微软所有的GitHub和OpenAI2021年10月,帮助编写软件程序更快。
“从今天开始,超过100个客户正在使用Mastercraft工具,”苏说。“我们并没有把ChatGPT-like数据模式智能解决方案。但最终当我们做,我们的愿景MasterCraft是(智能)low-code平台会成真。”
他说,TCS已经建立了一个内部使用病例使用生成人工智能解决方案,同时与全球合作伙伴。
在非常初期的项目,现在正在寻求利用巨大的内部代码,数据和资源,中国最大的软件服务公司。解决方案将通过内部构建算法,使用大型语言造型类似于生殖功能人工智能(AI)聊天机器人如ChatGPT但企业代码生成。
“我们看它的方式,它(生成AI)使用过去的代码,数据和经验学习,”苏告诉ET。”和许多年TCS已经在商业领域,我可以用我所有的知识作为基础。所以,如果技术使用和生成代码,我教使用TCS专有数据的算法,然后结果是我愿意许可。”
他说,TCS正在用例构建专有生成人工智能算法来构建代码和过程进一步成熟。他认为企业使用这些生成人工智能解决方案仍然需要整合的所有权和知识产权的产品,因此企业解决方案将会看到需求。
苏,明年5月退休,预计孟买软件公司推出的这些解决方案在任期即将结束时。“重点是构建模型和使用这些模型,生成的代码可以部署,”他说。
他说如果TCS想提供安全上下文生成人工智能解决方案加速客户项目,它不能只取决于多个大型语言工具从不同的提供者,但应该有自己的解决方案。
“每个人(客户)可以使用生成的人工智能。但是,作为一个供应商,我必须提供他们一些免费的任何侵权行为,和完整的知识产权的所有权,”苏说。
同时,该行业将不得不等待规定这些解决方案成熟进一步意识到技术的潜力,他说。
促使工程师
Subramaniam看到一个巨大的机会,在创建新角色组织内的“促使工程师”谁能有效沟通上下文查询大型语言模型为企业需求。
”的一件事,我们在市场上听到这就是你提示的问题生成人工智能平台是非常重要的,对吧?所以,我们即可形成一个角色被称为“促使工程师”组织内部,”他说。“我们尚未得到批准,但我们知道这个角色将作为重要的工程,数学或分析能力。”
TCS看到了一个机会将其生成AI提供与其low-code MasterCraft软件开发平台。
这将是类似于副驾驶——解决方案自动生成代码,由微软所有的GitHub和OpenAI2021年10月,帮助编写软件程序更快。
“从今天开始,超过100个客户正在使用Mastercraft工具,”苏说。“我们并没有把ChatGPT-like数据模式智能解决方案。但最终当我们做,我们的愿景MasterCraft是(智能)low-code平台会成真。”
他说,TCS已经建立了一个内部使用病例使用生成人工智能解决方案,同时与全球合作伙伴。
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