Mon.Oct 16, 2023

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Fine-Tuning, Retraining, and Beyond: Advancing with Custom LLMs

Analytics Vidhya

Introduction I’m pretty sure most of you have already used ChatGPT. That’s great because you’ve taken your first step on a journey we’re about to embark on in this article! You see, when it comes to mastering any new technology, the first thing you do is use it. It’s like learning to swim by jumping […] The post Fine-Tuning, Retraining, and Beyond: Advancing with Custom LLMs appeared first on Analytics Vidhya.

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Security Governance and Risk Management in Enterprise Architecture

Unite.AI

The digital landscape shifts daily, and with that comes an ever-evolving array of cyber threats. Businesses stand at a crossroads where the integration of security into enterprise architecture becomes not just beneficial but essential. The urgency is resonating, demanding immediate attention. Role of enterprise architecture in aligning IT with business objectives Enterprise architecture (EA) is the strategic nexus connecting IT solutions to overarching business aspirations.

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Harnessing NLP Superpowers: A Step-by-Step Hugging Face Fine Tuning Tutorial

Analytics Vidhya

Introduction Fine-tuning a natural language processing (NLP) model entails altering the model’s hyperparameters and architecture and typically adjusting the dataset to enhance the model’s performance on a given task. You can achieve this by adjusting the learning rate, the number of layers in the model, the size of the embeddings, and various other parameters.

NLP 329
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OpenAI Aims for a Bolder Presence in the Developer Arena

Unite.AI

OpenAI, a major player in the artificial intelligence sphere, is gearing up to introduce significant updates aimed at enhancing the developer experience. Sources from Reuters have hinted that these changes will not only simplify the development process but also make it more cost-effective for developers to craft and market AI-driven applications using OpenAI's suite of technologies.

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How To Get Promoted In Product Management

Speaker: John Mansour

If you're looking to advance your career in product management, there are more options than just climbing the management ladder. Join our upcoming webinar to learn about highly rewarding career paths that don't involve management responsibilities. We'll cover both career tracks and provide tips on how to position yourself for success in the one that's right for you.

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Enhancing Conversational AI with BERT: The Power of Slot Filling

Analytics Vidhya

Introduction In the era of Conversational AI, chatbots and virtual assistants have become ubiquitous, revolutionizing how we interact with technology. These intelligent systems can understand user queries, provide relevant information, and assist with various tasks. However, achieving accurate and context-aware responses is a complex challenge. One crucial component that aids in this process is slot […] The post Enhancing Conversational AI with BERT: The Power of Slot Filling appeared firs

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How to use audio data in LlamaIndex with Python

AssemblyAI

LlamaIndex is a flexible data framework for connecting custom data sources to Large Language Models (LLMs). With LlamaIndex, you can easily store and index your data and then apply LLMs.  LLMs only work with textual data, so to process audio files with LLMs we first need to transcribe them into text. Luckily, LlamaIndex provides an AssemblyAI integration through Llama Hub that lets you load audio data with just a few lines of code: from llama_hub.assemblyai.base import AssemblyAIAudioTransc

Python 200
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Six keys to achieving advanced container monitoring

IBM Journey to AI blog

Organizations have increasingly turned to containerization to create more scalable, efficient and agile infrastructure. Containerization involves packaging software code with the libraries and dependencies required to run the code. This creates self-contained code that can be run on any infrastructure, such as desktop, on-premises IT or cloud-native.

DevOps 214
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Bridging Large Language Models and Business: LLMops

Unite.AI

The underpinnings of LLMs like OpenAI's GPT-3 or its successor GPT-4 lie in deep learning, a subset of AI, which leverages neural networks with three or more layers. These models are trained on vast datasets encompassing a broad spectrum of internet text. Through training, LLMs learn to predict the next word in a sequence, given the words that have come before.

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How to use foundation models and trusted governance to manage AI workflow risk

IBM Journey to AI blog

Artificial intelligence (AI) adoption is still in its early stages. As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. Using AI for certain business tasks or without guardrails in place may also not align with an organization’s core values.

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Navigating the Future: Generative AI, Application Analytics, and Data

Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

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Elon Musk wants to merge humans with AI. How many brains will be damaged along the way?

Flipboard

Xinmei Liu for Vox The brain implant company Neuralink is pushing a needlessly risky approach, former employees say. Of all Elon Musk’s exploits — the Tesla cars, the SpaceX rockets, the Twitter takeover, the plans to colonize Mars — his secretive brain chip company Neuralink may be the most dangerous. What is Neuralink for? In the short term, it’s for helping people with paralysis.

AI 181
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Shedding light on AI bias with real world examples

IBM Journey to AI blog

As companies increase their use of artificial intelligence (AI), people are questioning the extent to which human biases have made their way into AI systems. Examples of AI bias in the real world show us that when discriminatory data and algorithms are baked into AI models, the models deploy biases at scale and amplify the resulting negative effects.

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Neural Networks’ Unique Perceptions: Decoding Machine vs. Human Sensory Recognition - Neuroscience News

Flipboard

A new study delves into the enigmatic realm of deep neural networks, discovering that while these models can identify objects akin to human sensory systems, their recognition strategies diverge from human perception.

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IBM Named a Leader in the 2023 Gartner Magic Quadrant for API Management

IBM Journey to AI blog

APIs serve as essential connectors between the growing number of data sources and applications in companies of all sizes and in all industries. This means that businesses are relying on and creating more APIs than ever before to get the data they need to power their applications and experiences, and scale their operations. However, it’s difficult to manage APIs manually, which is why organizations are turning to API management solutions like IBM API Connect® to bring consistency and s

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Understanding User Needs and Satisfying Them

Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.

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AI just spotted its 1st supernova. Could it replace human explosion hunters?

Flipboard

'Removing humans from the loop provides more time for the research team to analyze their observations and develop new hypotheses to explain the origin of the cosmic explosions that we observe.

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Challenges and risks associated with lack of real-time monitoring in SAP

IBM Journey to AI blog

Real-time monitoring in SAP BTP lets users harness the power of proactive detection and transform their operations, eliminating problems related to sluggish performance, downtime and troubleshooting errors. Real-time monitoring provides for a much-improved user experience, supporting swift action against performance degradation and prompt resolution of issues.

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Wall Street Watchdog Says AI to Cause 'Unavoidable' Economic Collapse

Flipboard

SEC Chairman Gary Gensler warns of an AI-driven financial disaster in next ten years. He doesn't think he can stop it. If regulators don't act now, Gensler says an economic meltdown is "nearly unavoidable.

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10 everyday machine learning use cases

IBM Journey to AI blog

Machine learning (ML)—the artificial intelligence (AI) subfield in which machines learn from datasets and past experiences by recognizing patterns and generating predictions—is a $21 billion global industry projected to become a $209 billion industry by 2029. Here are some real-world applications of machine learning that have become part of our everyday lives.

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How Embedded Analytics Gets You to Market Faster with a SAAS Offering

Start-ups & SMBs launching products quickly must bundle dashboards, reports, & self-service analytics into apps. Customers expect rapid value from your product (time-to-value), data security, and access to advanced capabilities. Traditional Business Intelligence (BI) tools can provide valuable data analysis capabilities, but they have a barrier to entry that can stop small and midsize businesses from capitalizing on them.

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Meta's unique approach to developing AI puzzles Wall Street, but techies love it

Flipboard

At Meta's annual Connect conference last month, virtual reality enthusiasts gathered to hear about Mark Zuckerberg's multibillion-dollar bet on the …

AI 180
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Llemma: An Open Language Model For Mathematics

Eleuther.ai

ArXiv | Models | Data | Code | Blog | Sample Explorer Today we release Llemma: 7 billion and 34 billion parameter language models for mathematics. The Llemma models were initialized with Code Llama weights, then trained on the Proof-Pile II, a 55 billion token dataset of mathematical and scientific documents. The resulting models show improved mathematical capabilities, and can be adapted to various tasks through prompting or additional fine-tuning.

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UK plan to lead in generative AI 'unrealistic,' say Cambridge researchers

Flipboard

The British government’s aim to turn the UK into a global leader in the development of generative AI is “unrealistic,” researchers at the University of Cambridge argue.

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Can Language Models Replace Programmers? Researchers from Princeton and the University of Chicago Introduce SWE-bench: An Evaluation Framework that Tests Machine Learning Models on Solving Real Issues from GitHub

Marktechpost

Evaluating the proficiency of language models in addressing real-world software engineering challenges is essential for their progress. Enter SWE-bench, an innovative evaluation framework that employs Python repositories’ GitHub issues and pull requests to gauge these models’ ability to tackle coding tasks and problem-solving. Surprisingly, the findings reveal that even the most advanced models can only handle straightforward issues.

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From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.

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5 Free Books to Master Data Science

Flipboard

Want to break into data science? Check this list of free books for learning Python, statistics, linear algebra, machine learning and deep learning.

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From 2D to 3D: Enhancing Text-to-3D Generation Consistency with Aligned Geometric Priors

Marktechpost

Converting 2D images into 3D objects for the purpose of text-to-3D generation is a daunting task. This is mainly because the 2D diffusion models learn only the view-agnostic priors and do not have an understanding of the 3D space during lifting. An outcome of this limitation is the multi-view inconsistency problem, i.e., the 3D object is not consistent from all viewpoints.

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From concept to patent: 4 key steps for AI entrepreneurs

Flipboard

In 2006, Research in Motion, the maker of the once-ubiquitous BlackBerry device, had to pay $612.5 million to a patent holding company, NTP.

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Unlocking AI Transparency: How Anthropic’s Feature Grouping Enhances Neural Network Interpretability

Marktechpost

In a recent paper, “Towards Monosemanticity: Decomposing Language Models With Dictionary Learning,” researchers have addressed the challenge of understanding complex neural networks, specifically language models, which are increasingly being used in various applications. The problem they sought to tackle was the lack of interpretability at the level of individual neurons within these models, which makes it challenging to comprehend their behavior fully.

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Embedding BI: Architectural Considerations and Technical Requirements

While data platforms, artificial intelligence (AI), machine learning (ML), and programming platforms have evolved to leverage big data and streaming data, the front-end user experience has not kept up. Holding onto old BI technology while everything else moves forward is holding back organizations. Traditional Business Intelligence (BI) aren’t built for modern data platforms and don’t work on modern architectures.

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Generative AI is everything, everywhere, all at once

Flipboard

Businesses want in on generative AI and are willing to do anything to ride the wave. Is generative AI here to stay? Most signs are pointing to yes.

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This AI Paper Introduces Lemur and Lemur Chat For Harmonizing Natural Language and Code For Language Agents

Marktechpost

In a broad sense, intelligent agents are autonomous problem solvers endowed with perception, judgment, and action capabilities based on data gathered from their surroundings. Recent applications of this idea have shown promise in developing language agents that can use natural language to do a wide range of complex tasks in various contexts. This is especially true when these agents are constructed using large language models (LLMs).

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Pras Michel of Fugees seeks new trial, contends former attorney used AI for closing argument

Flipboard

The hip-hop artist convicted on campaign finance and foreign influence charges seeks to set aside the jury’s guilty verdicts.

AI 176