Through natural language processing (NLP), machines are able to slowly evolve into understanding the way humans converse, emote, understand, respond, analyze and copy human conversations as well as sentiment-driven behaviors. NLP is the key technology behind chatbots, text-to-speech tools, voice recognition, virtual assistants, etc. In the pursuit of training machine learning modules into performing more complex tasks, there is a need for it to be trained with vast volumes of data using data annotation techniques. In case of NLP, the data annotation technique that’s applied is called text anno ..read more

What is Data Annotation? The assignment of attributes, tags or labels to data to assist machine learning algorithms in comprehending and classifying information that requires processing is known as data annotation. It plays a vital role in training artificial intelligence (AI) models and enabling machines in interpreting text, video, image or audio data. It also enables AI to learn and adapt. Hence, high quality AI training data is necessary for training AI models for producing results that are bias-free, representative and successful. Data annotation is not only necessary in model training ..read more

Large language models (LLMs) utilize computational artificial intelligence (AI) for producing language that is akin to human language. LLMs acquire training on vast quantities of text derived from the Internet for answering queries, providing summaries and creating stories or poems. The keywords are offered by the user for the LLMs to produce text on the given topics. One can also request a specific type of text which includes simplified language or poetry. In the medical world, LLMs have immense potential as communication plays an important role in patient care. Interpreting human spoken lang ..read more

The book “The Age of AI: And Our Human Future” written by Henry Kissinger, Eric Schmidt and Daniel Huttenlocker is about exploring the impact of artificial intelligence (AI) and the challenges it poses for humans. The book consists of many chapters with each chapter addressing the various aspects of the AI revolution. So, let’s start by understanding what AI actually means before diving deeper. AI or machine learning is a software system based on neural networks. AI can produce synthetic imagery and speech alongwith image and voice recognition. Research is ongoing for AI to browse web, book ti ..read more

Red Teaming can be described as a technique that can effectively remove vulnerabilities and enhance resiliency of Generative AI models. It is undoubtedly a great method for discovering and managing risks associated with Generative AI. The implementation of red teaming involves overcoming of several obstacles listed below. Clarification regarding what constitutes a red team Standardization of the team’s working during the testing of the model Specification regarding the codification of findings along with dissemination once the testing ends. Every model comprises of a distinct attack surface ..read more

Reinforcement Learning from Human Feedback (RLHF) involves training and fine-tuning large language models to perform a wide range of tasks like natural language generation, answering questions and generating codes. It involves combination of reinforcement learning with human feedback for training large language models (LLMs) to produce outputs that are informative and in alignment with human values. How LLMs trained on RLHF compare to traditional LLMs? RLHF for LLM Enhanced performance: It assists the LLMs into achieving enhanced performance on a range of tasks which include question answers ..read more

Logistics is a very chaotic and time-intensive industry. Artificial intelligence (AI) plays a key role in this industry by assisting the smooth transportation of goods from one location to another. It assists in enhancing, refining, and analysing supply chain operations. Logistics can be seen at play right from the manufacturing floor to the front door. Logistics is also a field that has abundant data along with scope for gathering more data. The creation of new AI solutions for supply chain disruptions involve consumption of a lot of resources. Since shipping and logistics need to be efficien ..read more

Today there is a pressing need for social media management in the online space due to the increasing one-on-one interaction with third parties. These third parties could be followers, customers, or just strangers. Content moderators have to ensure that real people get real response by screening online comments for profanity, obscenity, and offensive language on religion, political extremism, or even hate speech. Content moderation involves putting a control in place to moderate various types of content on social media platforms including Facebook, Twitter, LinkedIn or Tumbler, etc. which is n ..read more

Customization is very important for businesses to keep up with the race. Hence, Cogito offers detailed and customized data labeling services for Machine Learning and Artificial Intelligence. Today large language models (LLMs) have taken the center stage by revolutionizing AI digital interactions. Hence, it is of utmost importance to deploy accurate and qualitative data labeling techniques to ensure your AI model produces fresh and accurate output every time. Data labelers and vendors must supervise and blend data quality with human expertise to ensure ethical work practices. Creating a data re ..read more

Large language models (LLMs) over the past couple of years have shown unmatched potential when it comes to producing a variety of text from input prompts. But good text is something which cannot be defined easily as it is subjective and depends on context. Reinforcement Learning from Human Feedback (RLHF) utilizes techniques from reinforcement learning for direct optimization of a language model through human feedback. It has made it possible for language models to align a model which is trained on a general mass of text data over complex human values. RLHF deploys three model training process ..read more