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OpenAI API

We’re releasing an API for accessing new AI models developed by OpenAI. Unlike most AI systems which are designed for one use-case, the API today provides a general-purpose “text in, text out” interface, allowing users to try it on virtually any English language task. You can now request access

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FAQ

Why did OpenAI decide to release a commercial product?

Ultimately, what we care about most is ensuring artificial general intelligence benefits everyone. We see developing commercial products as one of the ways to make sure we have enough funding to succeed.

We also believe that safely deploying powerful AI systems in the world will be hard to get right. In releasing the API, we are working closely with our partners to see what challenges arise when AI systems are used in the real world. This will help guide our efforts to understand how deploying future AI systems will go, and what we need to do to make sure they are safe and beneficial for everyone.

Why did OpenAI choose to release an API instead of open-sourcing the models?

There are three main reasons we did this. First, commercializing the technology helps us pay for our ongoing AI research, safety, and policy efforts.

Second, many of the models underlying the API are very large, taking a lot of expertise to develop and deploy and making them very expensive to run. This makes it hard for anyone except larger companies to benefit from the underlying technology. We’re hopeful that the API will make powerful AI systems more accessible to smaller businesses and organizations.

Third, the API model allows us to more easily respond to misuse of the technology. Since it is hard to predict the downstream use cases of our models, it feels inherently safer to release them via an API and broaden access over time, rather than release an open source model where access cannot be adjusted if it turns out to have harmful applications.

What specifically will OpenAI do about misuse of the API, given what you’ve previously said about GPT-2?

With GPT-2, one of our key concerns was malicious use of the model (e.g., for disinformation), which is difficult to prevent once a model is open sourced. For the API, we’re able to better prevent misuse by limiting access to approved customers and use cases. We have a mandatory production review process before proposed applications can go live. In production reviews, we evaluate applications across a few axes, asking questions like: Is this a currently supported use case?, How open-ended is the application?, How risky is the application?, How do you plan to address potential misuse?, and Who are the end users of your application?.

We terminate API access for use cases that are found to cause (or are intended to cause) physical, emotional, or psychological harm to people, including but not limited to harassment, intentional deception, radicalization, astroturfing, or spam, as well as applications that have insufficient guardrails to limit misuse by end users. As we gain more experience operating the API in practice, we will continually refine the categories of use we are able to support, both to broaden the range of applications we can support, and to create finer-grained categories for those we have misuse concerns about.

One key factor we consider in approving uses of the API is the extent to which an application exhibits open-ended versus constrained behavior with regard to the underlying generative capabilities of the system. Open-ended applications of the API (i.e., ones that enable frictionless generation of large amounts of customizable text via arbitrary prompts) are especially susceptible to misuse. Constraints that can make generative use cases safer include systems design that keeps a human in the loop, end user access restrictions, post-processing of outputs, content filtration, input/output length limitations, active monitoring, and topicality limitations.

We are also continuing to conduct research into the potential misuses of models served by the API, including with third-party researchers via our academic access program. We’re starting with a very limited number of researchers at this time and already have some results from our academic partners at Middlebury Institute, University of Washington, and Allen Institute for AI. We have tens of thousands of applicants for this program already and are currently prioritizing applications focused on fairness and representation research.

How will OpenAI mitigate harmful bias and other negative effects of models served by the API?

Mitigating negative effects such as harmful bias is a hard, industry-wide issue that is extremely important. As we discuss in the GPT-3 paper and model card, our API models do exhibit biases that will be reflected in generated text. Here are the steps we’re taking to address these issues:

  • We’ve developed usage guidelines that help developers understand and address potential safety issues.
  • We’re working closely with users to understand their use cases and develop tools to surface and intervene to mitigate harmful bias.
  • We’re conducting our own research into manifestations of harmful bias and broader issues in fairness and representation, which will help inform our work via improved documentation of existing models as well as various improvements to future models.
  • We recognize that bias is a problem that manifests at the intersection of a system and a deployed context; applications built with our technology are sociotechnical systems, so we work with our developers to ensure they’re putting in appropriate processes and human-in-the-loop systems to monitor for adverse behavior.

Our goal is to continue to develop our understanding of the API’s potential harms in each context of use, and continually improve our tools and processes to help minimize them.

Updated September 18, 2020

Source: https://openai.com/blog/openai-api/

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A Quick Guide to Conversational AI And It’s Working Process

Customer support is an integral part of every business; without offering support services, it is difficult to achieve maximum customer satisfaction. To ensure the same, […]

The post A Quick Guide to Conversational AI And It’s Working Process appeared first on Quytech Blog.

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Customer support is an integral part of every business; without offering support services, it is difficult to achieve maximum customer satisfaction. To ensure the same, businesses hire professionals who work round the clock to deliver support services. No matter how efficiently a business handles this segment, they might have to face problems such as “delay in responding customers’ queries” or “making a customer wait to connect with the support professionals”, and more.

A Conversational AI is a perfect solution to this most common challenge that manufacturing, FMCG, retail, e-commerce, and other industries are facing. Never heard of this term?

Well, this is the latest trend in almost all the industries that are already using artificial intelligence technology or wanting to adopt the same in their business operations. Let’s read about the same in detail.

What is Conversational AI?

Conversational AI is a specific kind of artificial intelligence that makes software interact and converse with users in a highly intuitive way. It uses natural language processing (NLP) to understand and interact in human language.

The conversational AI, when integrated into chatbots, messengers, and voice assistants, enables businesses to deliver personalized customer experience and achieve 100% customer satisfaction. Google Home and Amazon Echo are the two popular examples of it.

Applications of Conversational AI

Conversational AI a new and automated way of offering customer support services. Healthcare, Adtech, logistics, insurance, travel, hospitality, finances, and other industries are using technology in the following:

Messaging applications

Conversational AI can be used in a messaging application to offer personalized support services through chat. Your customers can choose the “chat support” option and talk to the chatbot to get the support.

Speech-based virtual assistants

A conversational AI can use speech recognition technology so that you can offer a speech-based virtual assistant for your customers. These are the type of chatbots where users can get any information through voice commands.

Virtual customer assistants

This type of conversational AI helps in offering online support to customers; you can develop the same to offer support through Web, SMS, messaging applications, and more.

Virtual personal assistants

A virtual personal assistant, powered by conversational AI, minimizes the need of hiring a huge team to offer dedicated support services to each of your customers.

Virtual employee assistants

Employees working in big organizations might need various types of assistants. A conversational AI used to build a virtual employee assistant can be the point of contact for all such employees. They can find the required information just by interacting with that assistant.

Robotic process automation

Robotic process automation using the potential of conversational AI helps a machine to understand human conversations and their intent to perform automated tasks.

Working of conversational AI

Machine learning, deep learning, and natural language processing are the three main technologies behind conversational AI. Here is how it works:

  1. Collection of unstructured data from various sources
  2. Data preprocessing and feature engineering
  3. Creating an AI model
  4. Training the model to automatically improve from experiences
  5. Testing the model
  6. Detecting patterns and making decisions
  7. AI deployment

What benefits businesses can get by using conversational AI?

Apart from helping businesses to deliver an unmatched customer experience, conversational AI can offer a plethora of other benefits that include:

Saves Time

Having an automated chatbot would help you save a considerable amount of time. The saved time can be used to perform other tasks or focus on your business’ marketing and promotion.

Helps in providing Real-Time Support Services

A conversational AI can handle multiple queries at one time, without even letting other customers wait. In short, every customer will feel like they are getting dedicated support services in real-time.

Improves business efficiency

With a conversational AI, you can have the assurance that your customers are being taken care of properly. In short, their queries are being handled and resolved immediately. You can focus on other segments of your business and improve efficiency.

Helps in lowering down Customers’ Complaints

Since a conversational AI can immediately respond to queries of the customers, it can help to reduce the number of complaints. Resolving customers’ complaints without making them call a support professional would increase customer loyalty and increase your brand reputation.

Increases chances of sales

By providing a persistent communication channel that precedes the context further, you can make your customers explore more and shop more. Moreover, a conversational AI can also help in reducing the cart abandonment rate as it can provide immediate assistance regarding the issues a user is facing while making the payment, applying a discount code, or at any other time.

The user would not even have to contact the support center. To understand this better, let’s take an example- a user has added one or more products to the cart, but he/she is unable to find his/her preferred mode of payment. After a few minutes, what would the customer do, either visit the contact us section to get the customer support number and connect to a professional (which is a time taking process) or simply get the support through a conversational AI. The latter would automatically send a message to the customer to ask the query and provide a resolution.

Now when you know everything about conversational AI and want to build one for you, then contact Quytech, a trusted AI app development company. Quytech has more than a decade of experience in working on artificial intelligence, machine learning, and other latest technologies.

Final Words

Are you curious to know about conversational artificial intelligence? Give this article a read to know the definition and working of conversational AI in detail. We have also mentioned the reasons why this technology is becoming the talk of the town among businesses of all sizes and types. After reading the article, if you want to develop a tailor-made conversational AI for your business, then reach out to a reliable and experienced AI development company or hire AI developers with considerable experience.

Source: https://www.quytech.com/blog/what-is-conversational-ai-and-how-does-it-work/

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Are Legal chatbots worth the time and effort?

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KLoBot — the Best AI-Chatbot builder platform

The legal industry is always known for its resistance to change, but technology in the legal landscape has seen rapid growth from the past few years. The global Coronavirus pandemic has also accelerated the pace of investments in legal technology, which is likely to transform the legal marketplace.

Several law firms are majorly focusing on the adoption of innovative technology, which has the capability to modernize the practice of law. Innovative technologies, including Artificial Intelligence, Analytics, and Blockchain, among others, prioritizes the speed and efficiency of legal services.

Technology in the legal sector is an enabler that empowers attorneys and paralegals to perform their jobs better.

The use of AI and its applications in the legal industry is moving higher and is becoming the next big thing for legal firms. By 2024 the legal AI software market is expected to reach $1,236 million and is forecasted to grow at a CAGR of 31.3% during 2019–2024. (2)

Incorporating AI into legal practice can augment the workflows and streamline the work processes. AI-powered chatbots are disrupting the legal industry and are poised to become a preferred mode of communication for internal as well as external users. Leveraging NLP and NLU algorithm power, which are one of the prominent fields in AI, chatbots can understand intents, contexts, and further handle end to end human-machine interactions.

Law firms, as well as corporate legal departments, continue to look for new ways to enhance efficiency and drive productivity. AI-enabled chatbots are one such way that has the potential to revolutionize the law firm operations. These chatbots are a new approach for law firms to imitate human conversations and automatically respond to clients as well as attorneys’ queries.

Legal chatbots have the capabilities to make better and quicker decisions when compared to human agents. It reduces the burden on attorneys and paralegals to repetitively answer the same queries, which further brings consistency to users’ responses.

1. 8 Proven Ways to Use Chatbots for Marketing (with Real Examples)

2. How to Use Texthero to Prepare a Text-based Dataset for Your NLP Project

3. 5 Top Tips For Human-Centred Chatbot Design

4. Chatbot Conference Online

Internal Chatbots

Internal chatbots are nothing but the chatbots for internal operations and communications, helping law firms manage enterprise collaboration. Internal legal chatbots help law firms automate the contract review process, which is one of the most tedious tasks for attorneys and in-house counsel.

Legal chatbots for attorneys come with a predefined set of policies to review & analyze documents, perform due diligence, and automate other monotonous tasks that attorneys perform. Other basic tasks comprising scheduling meetings, setting up reminders, and searching relevant matter information can also be performed by legal chatbots. Internal legal chatbots empower attorneys to reduce the risk of human errors by automating the monotonous administrative chores and allow them to focus more on higher value and complicated tasks that need attorney’s intervention.

External Chatbots

External chatbots, on the other side, are the client-facing legal chatbots. These chatbots can draft the legal documents, including UCC filings, divorce forms, and other non-disclosure agreements based on the client inputs.

External legal chatbots empower law firms to handle the client intake process efficiently and generate leads, which further reduces an attorney’s time spent on these activities.

In the current scenario of receiving information instantly at a fingertip, legal chatbots serve as the best solution to handle client queries and provide legal advice.

External, as well as internal legal chatbots with their 24/7 supporting abilities, facilitate law firms to manage operational costs and meet the evolving client expectations.

Although chatbots are taking time to augment legal services but are worth the effort.

KLoBot is an incredibly intelligent AI chatbot builder platform that allows legal firms to create text and voice-based chatbots within minutes. KLoBot’s easy drag and drop skill interface helps law firms to design no-code chatbots that can be deployed across an organization’s favorite channels. The chatbots built on the KLoBot platform help law firms perform simple and complex routine tasks, including QnA and knowledge repository search. Few other jobs, including scheduling meetings, setting up reminders, completing actions on behalf of attorneys, finding colleagues, assisting attorneys, and much more, are also being performed by KLoBot enabled chatbots.

KLoBot enabled chatbots to act as a personal assistant and enhance attorneys as well as client experiences. These chatbots empower law firms to simplify internal as well as external communications and streamline business processes.

KLoBot AI chatbots with its feature-rich admin console, provide law firms robust security controls. To know more about KLoBot click here.

References

[1] The Law Society Capturing Technological Innovation in Legal Services Report

[2] https://www.marketsandmarkets.com/

Source: https://chatbotslife.com/are-legal-chatbots-worth-the-time-and-effort-5f44936f7e89?source=rss—-a49517e4c30b—4

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Inbenta Announces Partnership with IntelePeer to Deliver Smarter Workflows to Customers

Inbenta Technologies, a global leader in Symbolic AI-based Customer Interactions applications (artificial intelligence (AI) and natural language processing (NLP) products) announced today a new partnership with IntelePeer, a leading Communications Platform as a Service (CPaaS), provider. The combined partnership will empower users to build smarter and more powerful workflows so organizations can provide more innovative, […]

The post Inbenta Announces Partnership with IntelePeer to Deliver Smarter Workflows to Customers appeared first on Inbenta.

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New Product Offering Defines How Voice, Messaging and Chatbots Interoperate

Inbenta Technologies, a global leader in Symbolic AI-based Customer Interactions applications (artificial intelligence (AI) and natural language processing (NLP) products) announced today a new partnership with IntelePeer, a leading Communications Platform as a Service (CPaaS), provider. The combined partnership will empower users to build smarter and more powerful workflows so organizations can provide more innovative, agile, and scalable customer and employee support processes.

The Inbenta platform integrated with Atmosphere SmartFlows enables organizations to easily configure, automate, measure, and improve business interactions across multiple channels such as voice, SMS, Social Media and Enterprise Collaboration Platforms.  Customers will be able to use the intuitive drag and drop features, without any complicated coding. This will offload agent workload and create superior digital experiences.

“We are really happy to see this partnership going forward,” said Inbenta CEO Jordi Torras. “Combining the IntelePeer easy-to-use omni-channel platform with our Symbolic AI will empower our customers to build workflows across very different channels in a cohesive way, providing intelligence along the way.”

“With customer expectations on the rise and a constantly changing business climate, companies must stay ahead of the market with agile solutions,” said Jeremy Jones, IntelePeer’s Chief Commercial Officer. “We look forward to a successful partnership with Inbenta. With growing demand for more intelligent interactions, Inbenta’s AI helps detect customer’s intents, and respond with SmartFlows across different channels including voice, SMS, and social messaging to consistently stay ahead of the curve in a fast-changing digital business.”

About Inbenta

Inbenta was founded by Jordi Torras in Barcelona and is now headquartered in Silicon Valley. Inbenta empowers the world’s largest enterprise and e-commerce companies to improve customer satisfaction rates and reduce support costs with best-in-class functionality.

About IntelePeer

IntelePeer powers the new customer experience. Our Atmosphere® CPaaS  enables companies to communicate better – driving more revenue, improving their customer experience, and making better business decisions – leveraging omni-channel Automation & Self-Service, AI, and Analytics, all delivered through a single easy-to-use cloud platform that works seamlessly with your existing business solutions. For more information visit: www.intelepeer.com

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