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OpenAI Rolls Out Premium Data Connections for ChatGPT Users


The ChatGPT solution has become a transformative artificial intelligence solution widely adopted by individuals and businesses alike seeking to improve their operations. Developed by OpenAI, this sophisticated artificial intelligence platform has been proven to be very effective in assisting users with drafting compelling emails, developing creative content, or conducting complex data analysis by streamlining a wide range of workflows. 

OpenAI is continuously enhancing ChatGPT's capabilities through new integrations and advanced features that make it easier to integrate into the daily workflows of an organisation; however, an understanding of the platform's pricing models is vital for any organisation that aims to use it efficiently on a day-to-day basis. A business or an entrepreneur in the United Kingdom that is considering ChatGPT's subscription options may find that managing international payments can be an additional challenge, especially when the exchange rate fluctuates or conversion fees are hidden.

In this context, the Wise Business multi-currency credit card offers a practical solution for maintaining financial control as well as maintaining cost transparency. This payment tool, which provides companies with the ability to hold and spend in more than 40 currencies, enables them to settle subscription payments without incurring excessive currency conversion charges, which makes it easier for them to manage budgets as well as adopt cutting-edge technology. 

A suite of premium features has been recently introduced by OpenAI that aims to enhance the ChatGPT experience for subscribers by enhancing its premium features. There is now an option available to paid users to use advanced reasoning models that include O1 and O3, which allow users to make more sophisticated analytical and problem-solving decisions. 

The subscription comes with more than just enhanced reasoning; it also includes an upgraded voice mode that makes conversational interactions more natural, as well as improved memory capabilities that allow the AI to retain context over the course of a long period of time. It has also been enhanced with the addition of a powerful coding assistant designed to help developers automate workflows and speed up the software development process. 

To expand the creative possibilities even further, OpenAI has adjusted token limits, which allow for greater amounts of input and output text and allow users to generate more images without interruption. In addition to expedited image generation via a priority queue, subscribers have the option of achieving faster turnaround times during high-demand periods. 

In addition to maintaining full access to the latest models, paid accounts are also provided with consistent performance, as they are not forced to switch to less advanced models when server capacity gets strained-a limitation that free users may still have to deal with. While OpenAI has put in a lot of effort into enriching the paid version of the platform, the free users have not been left out. GPT-4o has effectively replaced the older GPT-4 model, allowing complimentary accounts to take advantage of more capable technology without having to fall back to a fallback downgrade. 

In addition to basic imaging tools, free users will also receive the same priority in generation queues as paid users, although they will also have access to basic imaging tools. With its dedication to making AI broadly accessible, OpenAI has made additional features such as ChatGPT Search, integrated shopping assistance, and limited memory available free of charge, reflecting its commitment to making AI accessible to the public. 

ChatGPT's free version continues to be a compelling option for people who utilise the software only sporadically-perhaps to write occasional emails, research occasionally, and create simple images. In addition, individuals or organisations who frequently run into usage limits, such as waiting for long periods of time for token resettings, may find that upgrading to a paid plan is an extremely beneficial decision, as it unlocks uninterrupted access as well as advanced capabilities. 

In order to transform ChatGPT into a more versatile and deeply integrated virtual assistant, OpenAI has introduced a new feature, called Connectors, which is designed to transform the platform into an even more seamless virtual assistant. It has been enabled by this new feature for ChatGPT to seamlessly interface with a variety of external applications and data sources, allowing the AI to retrieve and synthesise information from external sources in real time while responding to user queries. 

With the introduction of Connectors, the company is moving forward towards providing a more personal and contextually relevant experience for our users. In the case of an upcoming family vacation, for example, ChatGPT can be instructed by users to scan their Gmail accounts in order to compile all correspondence regarding the trip. This allows users to streamline travel plans rather than having to go through emails manually. 

With its level of integration, Gemini is similar to its rivals, which enjoy advantages from Google's ownership of a variety of popular services such as Gmail and Calendar. As a result of Connectors, individuals and businesses will be able to redefine how they engage with AI tools in a new way. OpenAI intends to create a comprehensive digital assistant by giving ChatGPT secure access to personal or organisational data that is residing across multiple services, by creating an integrated digital assistant that anticipates needs, surfaces critical insights, streamlines decision-making processes, and provides insights. 

There is an increased demand for highly customised and intelligent assistance, which is why other AI developers are likely to pursue similar integrations to remain competitive. The strategy behind Connectors is ultimately to position ChatGPT as a central hub for productivity — an artificial intelligence that is capable of understanding, organising, and acting upon every aspect of a user’s digital life. 

In spite of the convenience and efficiency associated with this approach, it also illustrates the need to ensure that personal information remains protected while providing robust data security and transparency in order for users to take advantage of these powerful integrations as they become mainstream. In its official X (formerly Twitter) account, OpenAI has recently announced the availability of Connectors that can integrate with Google Drive, Dropbox, SharePoint, and Box as part of ChatGPT outside of the Deep Research environment. 

As part of this expansion, users will be able to link their cloud storage accounts directly to ChatGPT, enabling the AI to retrieve and process their personal and professional data, enabling it to create responses on their own. As stated by OpenAI in their announcement, this functionality is "perfect for adding your own context to your ChatGPT during your daily work," highlighting the company's ambition of making ChatGPT more intelligent and contextually aware. 

It is important to note, however, that access to these newly released Connectors is confined to specific subscriptions and geographical restrictions. A ChatGPT Pro subscription, which costs $200 per month, is exclusive to ChatGPT Pro subscribers only and is currently available worldwide, except for the European Economic Area (EEA), Switzerland and the United Kingdom. Consequently, users whose plans are lower-tier, such as ChatGPT Plus subscribers paying $20 per month, or who live in Europe, cannot use these integrations at this time. 

Typically, the staggered rollout of new technologies is a reflection of broader challenges associated with regulatory compliance within the EU, where stricter data protection regulations as well as artificial intelligence governance frameworks often delay their availability. Deep Research remains relatively limited in terms of the Connectors available outside the company. However, Deep Research provides the same extensive integration support as Deep Research does. 

In the ChatGPT Plus and Pro packages, users leveraging Deep Research capabilities can access a much broader array of integrations — for example, Outlook, Teams, Gmail, Google Drive, and Linear — but there are some restrictions on regions as well. Additionally, organisations with Team plans, Enterprise plans, or Educational plans have access to additional Deep Research features, including SharePoint, Dropbox, and Box, which are available to them as part of their Deep Research features. 

Additionally, OpenAI is now offering the Model Context Protocol (MCP), a framework which allows workspace administrators to create customised Connectors based on their needs. By integrating ChatGPT with proprietary data systems, organizations can create secure, tailored integrations, enabling highly specialized use cases for internal workflows and knowledge management that are highly specialized. 

With the increasing adoption of artificial intelligence solutions by companies, it is anticipated that the catalogue of Connectors will rapidly expand, offering users the option of incorporating external data sources into their conversations. The dynamic nature of this market underscores that technology giants like Google have the advantage over their competitors, as their AI assistants, such as Gemini, can be seamlessly integrated throughout all of their services, including the search engine. 

The OpenAI strategy, on the other hand, relies heavily on building a network of third-party integrations to create a similar assistant experience for its users. It is now generally possible to access the new Connectors in the ChatGPT interface, although users will have to refresh their browsers or update the app in order to activate the new features. 

As AI-powered productivity tools continue to become more widely adopted, the continued growth and refinement of these integrations will likely play a central role in defining the future of AI-powered productivity tools. A strategic approach is recommended for organisations and professionals evaluating ChatGPT as generative AI capabilities continue to mature, as it will help them weigh the advantages and drawbacks of deeper integration against operational needs, budget limitations, and regulatory considerations that will likely affect their decisions.

As a result of the introduction of Connectors and the advanced subscription tiers, people are clearly on a trajectory toward more personalised and dynamic AI assistance, which is able to ingest and contextualise diverse data sources. As a result of this evolution, it is also becoming increasingly important to establish strong frameworks for data governance, to establish clear controls for access to the data, and to ensure adherence to privacy regulations.

If companies intend to stay competitive in an increasingly automated landscape by investing early in these capabilities, they can be in a better position to utilise the potential of AI and set clear policies that balance innovation with accountability by leveraging the efficiencies of AI in the process. In the future, the organisations that are actively developing internal expertise, testing carefully selected integrations, and cultivating a culture of responsible AI usage will be the most prepared to fully realise the potential of artificial intelligence and to maintain a competitive edge for years to come.

Google’s Med-Gemini: Advancing AI in Healthcare

Google’s Med-Gemini: Advancing AI in Healthcare

On Tuesday, Google unveiled a new line of artificial intelligence (AI) models geared toward the medical industry. Although the tech giant has issued a pre-print version of its research paper that illustrates the capabilities and methodology of these AI models, dubbed Med-Gemini, they are not accessible for public usage. 

According to the business, in benchmark testing, the AI models outperform the GPT-4 models. This specific AI model's long-context capabilities, which enable it to process and analyze research papers and health records, are one of its standout qualities.

Benchmark Performance

The paper is available online at arXiv, an open-access repository for academic research, and is presently in the pre-print stage. In a post on X (formerly known as Twitter), Jeff Dean, Chief Scientist at Google DeepMind and Google Research, expressed his excitement about the potential of these models to improve patient and physician understanding of medical issues. I believe that one of the most significant application areas for AI will be in the healthcare industry.”

The AI model has been fine-tuned to boost performance when processing long-context data. A higher quality long-context processing would allow the chatbot to offer more precise and pinpointed answers even when the inquiries are not perfectly posed or when processing a large document of medical records.

Multimodal Abilities

Text, Image, and Video Outputs

Med-Gemini isn’t limited to text-based responses. It seamlessly integrates with medical images and videos, making it a versatile tool for clinicians.

Imagine a radiologist querying Med-Gemini about an X-ray image. The model can provide not only textual information but also highlight relevant areas in the image.

Long-Context Processing

Med-Gemini’s forte lies in handling lengthy health records and research papers. It doesn’t shy away from complex queries or voluminous data.

Clinicians can now extract precise answers from extensive patient histories, aiding diagnosis and treatment decisions.

Integration with Web Search

Factually Accurate Results

Med-Gemini builds upon the foundation of Gemini 1.0 and Gemini 1.5 LLM. These models are fine-tuned for medical contexts.

Google’s self-training approach has improved web search results. Med-Gemini delivers nuanced answers, fact-checking information against reliable sources.

Clinical Reasoning

Imagine a physician researching a rare disease. Med-Gemini not only retrieves relevant papers but also synthesizes insights.

It’s like having an AI colleague who reads thousands of articles in seconds and distills the essential knowledge.

The Promise of Med-Gemini

Patient-Centric Care

Med-Gemini empowers healthcare providers to offer better care. It aids in diagnosis, treatment planning, and patient education.

Patients benefit from accurate information, demystifying medical jargon and fostering informed discussions.

Ethical Considerations

As with any AI, ethical use is crucial. Med-Gemini must respect patient privacy, avoid biases, and prioritize evidence-based medicine.

Google’s commitment to transparency and fairness will be critical in its adoption.

Phind-70B: Transforming Coding with Unmatched Speed and Precision

 

In the dynamic realm of technology, a luminary is ascending—Phind-70B. This transformative force in coding combines speed, intelligence, and a resolute challenge to GPT-4 Turbo, promising to redefine the coding paradigm. Rooted in the robust CodeLlama-70B foundation and fortified with an additional 50 billion tokens, Phind-70B operates at a breathtaking pace, impressively delivering a remarkable 80 tokens per second. 

It's not merely about velocity; Phind-70B excels in both rapidity and precision, setting it apart as a coding virtuoso. Distinctively, Phind-70B navigates intricate code and comprehends deep context with a 32K token window. This AI model isn't just about quick responses; it crafts high-quality, bespoke code aligned precisely with the coder's intent, elevating the coding experience to unparalleled heights. 

Numbers tell a compelling story, and Phind-70B proves its mettle by triumphing over GPT-4 Turbo in the HumanEval benchmark. While its score marginally lags in Meta's CRUXEval dataset, the real-world coding prowess of Phind-70B shines through, securing its place as a game-changing coding ally. At the heart of Phind-70B's triumph is TensorRT-LLM, a groundbreaking technology from NVIDIA, harnessed on the latest H100 GPUs. 

This not only propels Phind-70B to remarkable speed but ensures unparalleled efficiency, allowing it to think four times faster than its closest rival. Accessible to all, Phind-70B has forged strategic partnerships with cloud giants SF Compute and AWS. Coders can seamlessly embrace the coding future without cumbersome sign-ups, and for enthusiasts seeking advanced features, a Pro subscription is readily available. 

The ethos of the Phind-70B team is grounded in knowledge sharing. Their commitment is evident in plans to release weights for the Phind-34B model, with the ultimate goal of making Phind-70B's weights public. This bold move aims to foster community growth, collaboration, and innovation within the coding ecosystem. Phind-70B transcends its identity as a mere AI model; it signifies a monumental leap forward in making coding faster, smarter, and more accessible. 

Setting a new benchmark for AI-assisted coding with its unparalleled speed and precision, Phind-70B emerges as a revolutionary tool, an indispensable ally for developers navigating the ever-evolving coding landscape. The tech world resonates with anticipation as Phind-70B promises to not only simplify and accelerate but also elevate the coding experience. With its cutting-edge technology and community-centric approach, Phind-70B is charting the course for a new era in coding. Brace yourself to code at the speed of thought and precision with Phind-70B.

OpenAI: Turning Into Healthcare Company?


GPT-4 for health?

Recently, OpenAI and WHOOP collaborated to launch a GPT-4-powered, individualized health and fitness coach. A multitude of questions about health and fitness can be answered by WHOOP Coach.

It can answer queries such as "What was my lowest resting heart rate ever?" or "What kind of weekly exercise routine would help me achieve my goal?" — all the while providing tailored advice based on each person's particular body and objectives.

In addition to WHOOP, Summer Health, a text-based pediatric care service available around the clock, has collaborated with OpenAI and is utilizing GPT-4 to support its physicians. Summer Health has developed and released a new tool that automatically creates visit notes from a doctor's thorough written observations using GPT-4. 

The pediatrician then swiftly goes over these notes before sending them to the parents. Summer Health and OpenAI worked together to thoroughly refine the model, establish a clinical review procedure to guarantee accuracy and applicability in medical settings, and further enhance the model based on input from experts. 

Other GPT-4 applications

GPT Vision has been used in radiography as well. A document titled "Exploring the Boundaries of GPT-4 in Radiology," released by Microsoft recently, evaluates the effectiveness of GPT-4 in text-based applications for radiology reports. 

The ability of GPT-4 to process and interpret medical pictures, such as MRIs and X-rays, is one of its main uses in radiology. According to the report, "GPT-4's radiological report summaries are equivalent, and in certain situations, even preferable than radiologists."a

Be My Eyes is improving its virtual assistant program by leveraging GPT-4's multimodal features, particularly the visual input function. Be My Eyes helps people who are blind or visually challenged with activities like item identification, text reading, and environment navigation.

Many people have tested ChatGPT as a therapist when it comes to mental health. Many people have found ChatGPT to be beneficial in that it offers human-like interaction and helpful counsel, making it a unique alternative for those who are unable or reluctant to seek professional treatment.

What are others doing?

Both Google and Apple have been employing LLMs to make major improvements in the healthcare business, even before OpenAI. 

Google unveiled MedLM, a collection of foundation models designed with a range of healthcare use cases in mind. There are now two models under MedLM, both based on Med-PaLM 2, giving healthcare organizations flexibility and meeting their various demands. 

In addition, Eli Lilly and Novartis, two of the biggest pharmaceutical companies in the world, have formed strategic alliances with Isomorphic Labs, a drug discovery spin-out of Google's AI R&D division based in London, to use AI to find novel treatments for illnesses.

Apple, on the other hand, intends to include more health-detecting features in their next line of watches, concentrating on ailments like apnea and hypertension, among others.