IBM Journey to AI blog

OCTOBER 16, 2023

It encompasses risk management and regulatory compliance and guides how AI is managed within an organization. Foundation models: The power of curated datasets Foundation models , also known as “transformers,” are modern, large-scale AI models trained on large amounts of raw, unlabeled data.

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Unite.AI

SEPTEMBER 13, 2023

Increasingly though, large datasets and the muddled pathways by which AI models generate their outputs are obscuring the explainability that hospitals and healthcare providers require to trace and prevent potential inaccuracies. In this context, explainability refers to the ability to understand any given LLM’s logic pathways.

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IBM Journey to AI blog

AUGUST 12, 2024

The versatility of LLMs enables their application in diverse areas such as automated report generation, customer service chatbots, and compliance document analysis. Regulatory bodies emphasize the need for financial institutions to demonstrate how AI models make decisions, particularly in high-stakes areas like AML and BSA compliance.

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How to Learn Machine Learning

APRIL 4, 2025

AI will help to strengthen defences, cybercriminal departments will utilize AI to work against phishing and deepfake attacks. Explainable AI (XAI): As AI is expanding rapidly, there is a high demand for transparency and trust in AI-driven decisions. Thus, explainable AI (XAI) comes into the picture.

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Unite.AI

JANUARY 12, 2024

Enhancing user trust via explainable AI also remains vital. Addressing these technical obstacles will be key to unlocking multimodal AI's capabilities. Meta-learning Meta-learning, or ‘learning to learn', focuses on equipping AI models with the ability to rapidly adapt to new tasks using limited data samples.

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NVIDIA

MARCH 1, 2024

Developers of trustworthy AI understand that no model is perfect, and take steps to help customers and the general public understand how the technology was built, its intended use cases and its limitations. Topical guardrails ensure that chatbots stick to specific subjects.

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IBM Journey to AI blog

JULY 17, 2023

Generative AI has the potential to significantly disrupt customer care, leveraging large language models (LLMs) and deep learning techniques designed to understand complex inquiries and offer to generate more human-like conversational responses. Watsonx.data allows scaling of AI workloads using customer data. Watsonx.ai

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Towards AI

APRIL 2, 2024

X’s Grok Chatbot Will Soon Get an Upgraded Model, Grok-1.5 has announced an upgraded version of its AI model, Grok-1.5. This new model is expected to power the Grok chatbot on X. shows improved performance over the previous Grok-1 model on math and coding benchmarks. As per the official blog, Grok-1.5

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Dlabs.ai

JULY 19, 2023

The global tech leader had to enforce a ban on ChatGPT when it was discovered that employees had unintentionally revealed sensitive information to the chatbot. According to a Bloomberg report, proprietary source code had been shared with ChatGPT to check for errors, and the AI system was used to summarize meeting notes.

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NVIDIA

DECEMBER 13, 2023

Generative AI and large language models (LLMs), capable of learning meaning and context, promise disruptive capabilities across industries with new levels of output and productivity. Financial services firms can harness generative AI to develop more intelligent and capable chatbots and improve fraud detection.

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ODSC - Open Data Science

FEBRUARY 18, 2025

This is not science fiction, as these are the promises of PhD-level AI agentshighly autonomous systems capable of complex reasoning, problem-solving, and adaptive learning. Unlike traditional AI models, these agents go beyond pattern recognition to independently analyze, reason, and generate insights in specialized fields.

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ODSC - Open Data Science

SEPTEMBER 26, 2024

Using AI to Detect Anomalies in Robotics at the Edge Integrating AI-driven anomaly detection for edge robotics can transform countless industries by enhancing operational efficiency and improving safety. Where do explainable AI models come into play?

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ODSC - Open Data Science

JUNE 1, 2023

Generative AI May Help You Design Your New Game Character If legendary gaming studio Blizzard has its way, generative AI may be the next step in immersing in a game. Announcing the Free Generative AI Summit on July 20th To keep up with current trends, we’re hosting our first-ever Generative AI Summit, a free virtual event on July 20th.

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Snorkel AI

MARCH 19, 2024

In an ideal world, every company could easily and securely leverage its own proprietary data sets and assets in the cloud to train its own industry/sector/category-specific AI models. There are multiple approaches to responsibly provide a model with access to proprietary data, but pointing a model at raw data isn’t enough.

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Snorkel AI

MARCH 19, 2024

In an ideal world, every company could easily and securely leverage its own proprietary data sets and assets in the cloud to train its own industry/sector/category-specific AI models. There are multiple approaches to responsibly provide a model with access to proprietary data, but pointing a model at raw data isn’t enough.

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Pickl AI

APRIL 8, 2024

Overhyped Expectations The media and tech companies often portray AI as a revolutionary technology capable of solving all our problems. This can lead to unrealistic expectations and disappointment when AI fails to live up to the hype. Example In 2016, a chatbot developed by Microsoft called Tay was launched on Twitter.

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Viso.ai

JULY 9, 2024

Understanding Generative AI Generative AI refers to the class of AI models capable of generating new content depending on an input. Text-to-image for example, refers to the ability of the model to generate images from a text prompt. Text-to-text models can produce text output based on a text prompt.

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Heartbeat

SEPTEMBER 7, 2023

Let’s start by understanding why transparency in AI is not just an option but a necessity in today’s world. The Need for Model Interpretability and Explainability In the age of AI, models impact our lives in countless ways. Consider healthcare, where AI models are being used for disease diagnosis.

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How to Learn Machine Learning

JANUARY 21, 2023

AI-powered health and fitness apps can help us to monitor our physical activity and health, and to make more informed decisions about our lifestyle. AI-powered entertainment systems can also provide us with personalized content recommendations and virtual reality experiences.

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Viso.ai

MARCH 26, 2024

These systems rely on AI models, like CNNs, for image recognition and recurrent neural networks ( RNNs ) for voice pattern analysis. In turn, these models are typically developed using frameworks like TensorFlow and Keras. Overcoming the ‘black box’ nature of AI for transparent and explainable AI systems.

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The MLOps Blog

FEBRUARY 27, 2025

Transparency can be achieved by providing contextual insights into model outputs. Picture this: youve spent months fine-tuning an AI-powered chatbot to provide mental health support. She remarked: The regulatory focus, especially in the draft AI Act, is less on the internal structure of the algorithms (i.e.,

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Marktechpost

JULY 11, 2023

LLMs, the Artificial Intelligence models that are designed to process natural language and generate human-like responses, are trending. The best example is OpenAI’s ChatGPT, the well-known chatbot that does everything from content generation and code completion to question answering, just like a human.

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IBM Journey to AI blog

SEPTEMBER 3, 2024

And while organizations are taking advantage of technological advancements such as generative AI , only 24% of gen AI initiatives are secured. This lack of security threatens to expose data and AI models to breaches, the global average cost of which is a whopping USD 4.88 Choose energy-efficient AI models or frameworks.

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Pickl AI

APRIL 2, 2024

Use it for sentiment analysis, topic modeling, and building chatbots. Explainable AI (XAI): As AI models become more complex, there’s a growing need for interpretability. XAI techniques will help us understand how models arrive at their decisions.

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IBM Journey to AI blog

FEBRUARY 9, 2024

iii] “AI models haven’t had that kind of data before. Those models will just have a better understanding of everything.” They make AI more explainable: the larger the model, the more difficult it is to pinpoint how and where it makes important decisions.

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