Today, we are proud to announce the launch of AutoAlign™, a platform to help enterprises develop and test generative AI models before they hit the
Since launching Armilla, we’ve witnessed an increasing lack of trust in AI products. The trust deficit is making it harder for even the most responsible companies to sell high-quality, reliable AI products that deserve to be trusted on their merits.
The public emergence of generative AI over the past few months has revealed how, for better and for worse, large language models (LLMs) like ChatGPT are poised to revolutionize significant portions of our economy.
I’ve been playing around with the new Bing search engine that has incorporated Open AI’s Large Language Model (LLM). This is a custom model that seems more advanced than GPT 3.5 to me, which some folks are calling Sydney and internally Microsoft seems to call Prometheus.
Today, we are proud to announce the launch of AutoAlign™, a platform to help enterprises develop and test generative AI models before they hit the
Since launching Armilla, we’ve witnessed an increasing lack of trust in AI products. The trust deficit is making it harder for even the most responsible companies to sell high-quality, reliable AI products that deserve to be trusted on their merits.
The public emergence of generative AI over the past few months has revealed how, for better and for worse, large language models (LLMs) like ChatGPT are poised to revolutionize significant portions of our economy.
I’ve been playing around with the new Bing search engine that has incorporated Open AI’s Large Language Model (LLM). This is a custom model that seems more advanced than GPT 3.5 to me, which some folks are calling Sydney and internally Microsoft seems to call Prometheus.
For this reason, the HR sector has become one of the most rapid adopters of AI/ML technologies, which have brought new levels of efficiency to nearly all aspects of the traditional HR pipeline.
Through this new partnership, Armilla AI will work alongside Mila to pioneer applied AI testing and validation research methods to improve model performance while addressing key issues related to fairness, bias, explainability and robustness.
What nearly all AI failures share in common is that they tend to arise due to inadequate quality and robustness testing.
According to Forbes, all Fortune 500 companies report using some form of automation in their HR pipelines. And it’s not just large companies that are jumping on this trend: industry surveys have shown that at least 25% of all US-based companies plan to increase their use of automated systems in hiring and talent management over the next few years.
As the technology becomes more powerful, we need to proactively invest in the verification, validation, control, and monitoring of these systems. There is too much at stake to not do so.
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