Large language models aren’t always more complex


Language models such as OpenAI’s GPT-3, which leverage AI techniques and large amounts of data to learn skills like writing text, have received an increasing amount of attention from the enterprise in recent years. From a qualitative standpoint, the results are good — GPT-3 and models inspired by it can write emails, summarize text, and even generate code for deep learning in Python. But some experts are skeptical that the size of these models — and their training datasets — correspond to performance.

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Foundation models risk exacerbating ML’s ethical challenges 

Machine learning is undergoing a paradigm shift with the rise of models trained at massive scale, including Google’s BERT, OpenAI’s DALL-E, and AI21 Labs’ Jurassic-1 Jumbo. Their capabilities and dramatic performance improvements are leading to a new status quo: a single model trained on raw datasets that can be adapted for a wide range of applications. Indeed, OpenAI is reportedly developing a multimodal system trained on images, text, and other data using massive computational resources, which the company’s leadership believes is the most promising path toward AGI — AI that can learn any task a human can.

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AI datasets are prone to mismanagement, study finds

AI datasets

Public datasets like Duke University’s DukeMTMC are often used to train, test, and fine-tune machine learning algorithms that make their way into production, sometimes with controversial results. It’s an open secret that biases in these datasets could negatively impact the predictions made by an algorithm, for example causing a facial recognition system to misidentify a person. But a recent study coauthored by researchers at Princeton reveals that computer vision datasets, particularly those containing images of people, present a range of ethical problems.

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Forrester: Adopting fraud-fighting AI requires the right technical framework

Lock on a circuit board

AI tools have become part and parcel of fraud management solutions in the enterprise, according to a new Forrester report. In it, analysts at the firm identify key fraud management use cases where AI can help, mapping how brands can deploy AI technologies in each scenario.

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IDC: AI spending will reach $342B in 2021

Woman looking at a maze

Companies could spend nearly $342 billion on AI software, hardware, and services in 2021. That’s according to the latest edition of IDC’s Worldwide Semiannual Artificial Intelligence Tracker, which found that the AI market is forecast to accelerate in 2022 with 18.8% growth and remain on track to break the $500 billion mark by 2024.

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97% of execs say data science is ‘crucial’ to maintaining profitability


Ninety-seven percent of U.S. data executives say data science is crucial to maintaining profitability and boosting the bottom line. However, nearly as many say that flawed approaches to data science strategy, execution, and staffing make achieving that goal difficult.

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Researchers open-source benchmarks measuring quality of AI-generated code

Code conversion

In recent years, large-scale AI language models have shown promise in generalizing to tasks including writing code, implying that humans’ work may be one day supplemented by AI systems. But while some studies show that language models can translate code and fix compilation issues, there’s been little work on rigorously testing the coding ability of models given general coding problems.

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The AI industry is built on geographic and social inequality, research shows

The arm of global inequality is long, rendering itself visible particularly in the development of AI and machine learning systems. In a recent paper, researchers at Cornell, the Universite de Montreal, the National Institute of Statistical Sciences (U.S.), and Princeton argue that this inequality in the AI industry involves a concentration of profits and raises the danger of ignoring the contexts to which AI is applied.

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EU human rights agency issues report on AI ethical considerations

The European Union’s Fundamental Rights Agency (FRA) has issued a report on AI which delves into the ethical considerations which must be made about the technology. FRA’s report is titled Getting The Future Right and opens with some of the ways AI is already making lives better—such as helping with cancer diagnosis, and even predicting…

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State of European Tech: Investment in ‘deep tech’ like AI drops 13%

The latest State of European Tech report highlights that investment in “deep tech” like AI has dropped 13 percent this year. Data from Dealroom was used for the State of European Tech report. Dealroom defines deep tech as 16 fields: Artificial Intelligence, Machine Learning, Big Data, Augmented Reality, Virtual Reality, Drones, Autonomous Driving, Blockchain, Nanotech…

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Deloitte’s 2020 State of AI in the Enterprise study, 3rd Edition

For the third straight year, Deloitte surveyed executives about their companies’ sentiments and practices regarding AI technologies. We were particularly interested in understanding what it will take to stay ahead of the pack as AI adoption grows – and we wanted to learn how adopters are managing risk around the technologies as AI governance, trust, and ethics become more of a boardroom issue.

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Stanford and Carnegie Mellon find race and age bias in mobility data that drives COVID-19 policy

Smartphone-based mobility data has played a major role in responses to the pandemic. Describing the movement of millions of people, location information from Google, Apple, and others has been used to analyze the effectiveness of social distancing polices and probe how different sectors of the economy have been affected.

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AI helps patients to get more rest while reducing staff workload

A team from Feinstein Institutes for Research thinks AI could be key to helping patients get more rest while reducing the burden on healthcare staff. Everyone knows how important adequate sleep is for recovery. However, patients in pain – or just insomniacs like me – can struggle to get the sleep they need. “Rest is…

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Oracle Global Study: 82% of people believe Robots can support their Mental Health better than humans

2020 has been the most stressful year in history for the global workforce and people want robots to help, according to a new study by Oracle and Workplace Intelligence, an HR research and advisory firm. The study of more than 12,000 employees, managers, HR leaders, and C-level executives across 11 countries found that the COVID-19 pandemic has increased workplace stress, anxiety, and burnout for people all around the world, and they prefer robots instead of other people to help.

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IBM study highlights rapid uptake and satisfaction with AI chatbots

A study by IBM released this week highlights the rapid uptake of AI chatbots in addition to increasing customer satisfaction. Most of us are hardwired to hate not speaking directly to a human when we have a problem—following years of irritating voicemail systems. However, perhaps the only thing worse is being on hold for an…

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Google researchers investigate how transfer learning works

Transfer learning’s promise of storing knowledge gained while solving a problem and applying it to a related problem has attracted considerable attention. But despite recent breakthroughs, no one fully understands what enables a successful transfer and which parts of algorithms are responsible for it.

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IBM uses AI to evaluate risk of developing genetic diseases

In a study published in the journal Nature Communications, scientists at IBM, the Broad Institute of MIT and Harvard, and health tech company Color find evidence the presence of genetic mutations isn’t a reliable precursor to genetic diseases. They claim diseases can so greatly be influenced by other factors that the risk in carriers is sometimes as low as that of noncarriers.

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Intel details robotic assistive arm for wheelchair users

Intel today detailed a collaboration with Accenture and the ALYN Woldenberg Family Hospital (the Neuro-Biomorphic Engineering Lab at the Open University of Israel), to develop a wheelchair-mounted robotic arm that helps people with spinal injuries perform daily tasks.

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Research shows natural language benchmarks don’t measure AI models’ general knowledge well

Cloud network

Open-domain question-answering has received attention in the AI community for its practical applications. But a deep understanding of what kinds of questions models can answer remains elusive; unknowns make it hard to contextualize the results.

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Researchers claim bias in AI named entity recognition models

Twitter researchers claim to have found evidence of demographic bias in named entity recognition. They say their analysis reveals AI performs better at identifying names from specific groups, and the biases manifest in syntax, semantics, and how word uses vary across linguistic contexts.

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