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Top Deep Learning Companies in Australia

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60 companies for Deep Learning in Australia

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DeepAi's Logo

DeepAi

Sydney, Australia

A

1-10 Employees

2020

Key takeaway

Deep Ai is a leading technology recruitment agency in Sydney that specializes in connecting companies with top tech talent, ensuring that businesses can make successful hires. Their extensive talent pool and expertise in the tech sector position them as a valuable partner for organizations looking to build world-class teams.

Reference

Core business

Home - Deep AI

Connecting you with the best Tech Talent in Australia SEARCH JOBS We build world-class tech teams Deep Ai is Australia’s leading Tech Talent specialist. Our In-demand Talent Pool will give you 100% confidence that you are receiving the best candidate for the role. Competition can be fierce and making the right hire can make all […]

BrewAI's Logo

BrewAI

Sydney, Australia

A

51-100 Employees

2020

Key takeaway

BrewAI offers a powerful deep learning automl product that enables businesses to easily build optimized neural networks and predictive engines without any coding. Their technology focuses on making AI accessible and user-friendly, allowing organizations to adopt deep learning solutions quickly and efficiently, ultimately driving business outcomes.

Reference

Core business

Commercial Grade Deep Learning Tooling - BrewAI

BIZDATA PTY LTD's Logo

BIZDATA PTY LTD

Melbourne, Australia

A

11-50 Employees

2005

Key takeaway

BizData is an award-winning Data Analytics Agency that specializes in the rapid delivery of Artificial Intelligence and Machine Learning solutions. They focus on transforming operational data into accessible products, promoting a data-driven culture that enhances customer experiences.

Reference

Product

Machine Learning

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Inject AI's Logo

Inject AI

Adelaide, Australia

A

1-10 Employees

-

Key takeaway

The company has over 25 years of experience in applying machine learning across various applications, including object detection, tracking, and vision-and-language processing, which are all relevant to deep learning. They also focus on simplifying AI and maximizing its value for businesses, suggesting expertise in integrating advanced models like ChatGPT.

Reference

Core business

InjectAI

Machine learning and AI Solutions Company

Cognr - AI & Data Science's Logo

Cognr - AI & Data Science

Melbourne, Australia

A

1-10 Employees

-

Key takeaway

The company is focused on leveraging AI, Data, and Machine Learning to create innovative, hyper-personalized solutions that enhance organizational efficiency. They emphasize the importance of developing autonomous business solutions and are actively seeking talent in various AI sub-fields, underscoring their commitment to advancing technologies like Deep Learning.

Reference

Core business

Cognr | AI Solutions & Consulting

Autonomous business solutions harnessing the power of Data, Machine Learning and Artificial Intelligence

Cloud Bio-Logic's Logo

Cloud Bio-Logic

Greater Brisbane, Australia

A

1-10 Employees

2014

Key takeaway

Cloud Bio-Logic utilizes state-of-the-art neural network deep learning algorithms to perform real-time, patient-specific multivariate analysis, enhancing the accuracy and precision of medical diagnostics and therapeutics. Their innovative computational methods and custom hardware ensure low latency, making it a pivotal player in advancing medical practice through technology.

Reference

Core business

Medical | Cloud Bio-Logic

Cloud Bio-Logic is a ​state-of-the-art neural network deep learning artificial intelligence system performing on-demand, patient-specific, real-time, dynamic Bayesian network multivariate analysis for medical diagnostics.

Matrix AI's Logo

Matrix AI

Sydney, Australia

A

1-10 Employees

2014

Key takeaway

Matrix AI is a Sydney-based company that specializes in end-to-end machine learning application development services, highlighting their expertise in deploying machine-learning infrastructure at scale. Their core product, Matrix OS, is designed to enhance cloud and machine learning operations, making it relevant to the field of deep learning.

Reference

Core business

Matrix AI

Matrix AI is a Sydney based company that provides end to end machine learning application development services. We deliver full stack software solutions to automate your business processes.

bluebeak.ai's Logo

bluebeak.ai

Greater Brisbane, Australia

A

1-10 Employees

2018

Key takeaway

Bluebeak is at the forefront of machine learning innovation, leveraging the latest technologies to provide world-class AI solutions. As a trusted Google Cloud Partner, Bluebeak focuses on developing advanced data science tools that enhance the implementation of AI at scale.

Reference

Core business

Bluebeak.ai | Machine Learning & Data Science Platform

Bluebeak.ai | Machine Learning & Data Science Platform

SenseDeep's Logo

SenseDeep

Melbourne, Australia

A

11-50 Employees

2019

Key takeaway

SenseDeep focuses on providing real-time insights and feedback for development teams, which can be crucial in optimizing and accelerating the delivery of serverless applications.

Reference

Core business

SenseDeep Open Source | SenseDeep

Prophetico's Logo

Prophetico

Sydney, Australia

A

51-100 Employees

2019

Key takeaway

Lakeba has developed an AI-driven neural network that utilizes deep learning to identify business challenges and provide innovative technology solutions. This system supports their business model by offering automated, intelligent predictive reports.

Reference

Core business

Prophetico | Automated intelligent predictive reports

A World first AI-driven neural network designed to expose business challenges in need of new technology solutions.


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Products and services for Deep Learning

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Use cases around Deep Learning

A selection of suitable use cases for products or services provided by verified companies according to your search.

UseCase: EU-AI Act

Use case

EU-AI Act

All industries, Pharma, Finance, E-Mobility, Healthcare

er EU AI Act klassifiziert KI-Systeme in 4 Risikostufen: Verbotene KI: Soziale Bewertungssysteme, biometrische Echtzeit-Überwachung, manipulative Systeme Hochrisiko-KI: Kritische Infrastruktur, Bildung, Personalwesen, wichtige Dienste, Strafverfolgung Begrenzte Risiken: Chatbots (Transparenzpflicht), KI-generierte Inhalte (Kennzeichnungspflicht), Emotionserkennung Minimales Risiko: Alle anderen KI-Anwendungen ohne spezifische Auflagen Nachweis KI-Kompetenz: Unternehmen müssen dokumentieren, dass ihre KI-Systeme konform sind Verpflichtende Schulungen für Mitarbeiter im Umgang mit KI-Systemen Nachweis technischer Expertise im Entwicklungsteam Regelmäßige Überprüfung und Aktualisierung der KI-Kompetenzen Dokumentation von Risikobewertungen und Qualitätsmanagement Etablierung eines KI-Ethik-Boards für Hochrisiko-Anwendungen Inkrafttreten: 24 Monate nach Verabschiedung, Hochrisiko-Systeme: 36 Monate Übergangsfrist. Ziel ist ein sicherer, ethischer KI-Einsatz in der EU durch kompetente Anwendung und Überwachung.

UseCase: EU-AI Act

Use case

EU-AI Act

All industries, Pharma, Finance, E-Mobility, Healthcare

er EU AI Act klassifiziert KI-Systeme in 4 Risikostufen: Verbotene KI: Soziale Bewertungssysteme, biometrische Echtzeit-Überwachung, manipulative Systeme Hochrisiko-KI: Kritische Infrastruktur, Bildung, Personalwesen, wichtige Dienste, Strafverfolgung Begrenzte Risiken: Chatbots (Transparenzpflicht), KI-generierte Inhalte (Kennzeichnungspflicht), Emotionserkennung Minimales Risiko: Alle anderen KI-Anwendungen ohne spezifische Auflagen Nachweis KI-Kompetenz: Unternehmen müssen dokumentieren, dass ihre KI-Systeme konform sind Verpflichtende Schulungen für Mitarbeiter im Umgang mit KI-Systemen Nachweis technischer Expertise im Entwicklungsteam Regelmäßige Überprüfung und Aktualisierung der KI-Kompetenzen Dokumentation von Risikobewertungen und Qualitätsmanagement Etablierung eines KI-Ethik-Boards für Hochrisiko-Anwendungen Inkrafttreten: 24 Monate nach Verabschiedung, Hochrisiko-Systeme: 36 Monate Übergangsfrist. Ziel ist ein sicherer, ethischer KI-Einsatz in der EU durch kompetente Anwendung und Überwachung.

Information about Deep Learning in Australia

When exploring the Deep Learning industry in Australia, several key considerations emerge. The regulatory landscape is crucial, as compliance with data privacy laws such as the Australian Privacy Principles is essential for any company working with large datasets. Understanding the local talent pool is also important; Australia boasts a strong educational framework, producing skilled professionals in data science and machine learning, but competition for this talent is intense, necessitating attractive employment packages and work environments. Opportunities abound in sectors like healthcare, agriculture, and finance, where deep learning applications can drive efficiency and innovation. However, challenges such as data availability and quality can hinder development and implementation. The competitive landscape features several startups and established companies, necessitating awareness of both local players and global firms that may enter the market. Environmental concerns, particularly in relation to the energy consumption of training deep learning models, are becoming increasingly relevant, prompting a shift towards sustainable practices. Lastly, Australia’s position in the global market is significant, with potential for collaboration on international projects, making it an attractive location for investment in deep learning technology. Understanding these factors provides valuable insights for anyone interested in this evolving field.


Insights about the Deep Learning results above

Some interesting numbers and facts about your company results for Deep Learning

Country with most fitting companiesAustralia
Amount of fitting manufacturers318
Amount of suitable service providers343
Average amount of employees1-10
Oldest suiting company2005
Youngest suiting company2020

Frequently asked questions (FAQ) about Deep Learning Companies

Some interesting questions that has been asked about the results you have just received for Deep Learning

Based on our calculations related technologies to Deep Learning are Big Data, E-Health, Retail Tech, Artificial Intelligence & Machine Learning, E-Commerce

The most represented industries which are working in Deep Learning are IT, Software and Services, Education, Other, Consulting, Marketing Services

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Deep Learning results by various countries

Related categories of Deep Learning