This article reports on the third iteration of a survey of computerized tools and technologies taught as part of postgraduate translation training programmes. While the survey was carried out under the aegis of the EMT Network, more than half of responses are from outside that network. The results show the responsiveness of programmes to innovations in translation technology, with increased compulsory inclusion of machine translation, post-editing, and quality evaluation, and a rapid response to the release of generative tools. The flexibility required during the Covid-19 pandemic has also led to some lasting changes to programmes. While the range of tools being taught has continued to expand, programmes seem to be consolidating their core offering around cloud-based software with cost-free academic access. There has also been an increase in the embedding of professional contexts and workflows associated with translation technology. Generic file management and data security skills have increased in perceived importance, and legal and ethical issues related to translation data have also become more prominent. In terms of course delivery the shift away from conventional labs identified in EMT2017 has accelerated markedly, no doubt partly driven by the pandemic, accompanied by a dramatic expansion in the use of students' personal devices.

If you're subscribed to Amazon Prime Video, it's likely you've seen'Space Cadet' promoted at the top of your feed this week. The movie has raced to the top of the charts and sees Emma Roberts star as a trainee astronaut at NASA. In the film, Roberts' character, Rex, manages to make it on to NASA's training programme by faking her CV. However, in reality, it's much trickier to be selected, with just 360 lucky candidates making the cut at the US space agency since the 1960s. So, do you have what it takes to become an astonaut?

CMR Surgical has launched a data-led training programme for its Versius surgical robot system, with the intention of reducing overall training time and improving standardisation in surgical care. The seven-step programme uses data-driven metrics and benchmarking to assess skill levels. This data is captured through the training technology tools and standard observational data, and supports personalised feedback. As a result it is expected that learning curves will be shorter, minimising the cost and time for teams to become proficient. At the same time, the data can help to standardise surgeries with a view to improving outcomes for patients.

NITI Aayog, back in June 2018, released the National Strategy on Artificial Intelligence, and now PM Narendra Modi launched the'AI for All' initiative by CBSE. An approach towards fulfilling NEP 2020 objectives, the government seems keen to have youth ready for the future. "I personally view'AI for All' representing both sides of the coin: the equitable access to AI skills, as well as the equitable deployment of AI technologies. In a diverse country like ours, with citizens across different literacy levels and economic strata, both of these are extremely important," said Vineeth N Balasubramanian, Head of AI Dept., IIT-Hyderabad. Being the third-largest economy in terms of Purchasing Power Parity (PPP), the second-highest number of engineering graduates, and the world's highest data usage per smartphone -- India's low number of academic, corporate peer-reviewed AI publications do not justify its potential.

The Government of Ireland released its national AI strategy on Thursday 8th July 2021, presenting it online, with key members of the government and the public sector in attendance. Comprising a 73-page document, the strategy considers AI from three different perspectives: building public trust in AI, leveraging AI for economic and societal benefit, and enablers for AI. These key aspects are detailed in the strategy document, with eight actionable corresponding strands ranging from how to engage and raise awareness of the public about AI, to building a strong AI innovation ecosystem, to nurturing and developing AI skills and talents. Following the European approaches of ethical, human-centred, and trustworthy AI, "The National AI Strategy will serve as a roadmap to an ethical, trustworthy and human-centric design, development, deployment and governance of AI to ensure Ireland can unleash the potential that AI can provide," writes Robert Troy, Minister of State for Trade Promotion, Digital and Company Regulation. "Underpinning our Strategy are three core principles to best embrace the opportunities of AI – adopting a human-centric approach to the application of AI; staying open and adaptable to innovations; and ensuring good governance to build trust and confidence for innovation to flourish, because ultimately if AI is to be truly inclusive and have a positive impact on all of us, we need to be clear on its role in our society and ensure that trust is the ultimate marker of success."

Today's evolving business landscape puts organizations under constant pressure to innovate. This has made digital transformation a top priority for businesses. For some, digital transformation efforts are yielding positive results. However, many companies are struggling to reap the benefits of digital transformation, as becoming a digital enterprise is no small undertaking. It requires comprehensive, systemic change.

The world is inundated with data. Take just the global financial markets. They generate vast amounts of data – share prices, commodity prices, indices, option and futures prices, to name just a few. But data is of no use if there aren't people able to collect, collate, analyse and apply it to the benefit of society. All that data generated by global financial markets gets used for asset and wealth management – and it must be properly analysed and understood to inform good decision making.

Waves of disruptive technologies have fostered creativity, innovation and ease of communication, but they are also a catalyst of potentially massive job losses, with machines set to take over jobs once done by humans. SCB workers walk past the front of the bank's head office on Ratchadaphisek Road. While forecasts of future job losses from artificial intelligence (AI) and automation have mushroomed, tangible damage has already been done to certain industries. In a massive restructuring, US auto giant General Motors has announced it will cut 15% of its 180,000-strong workforce to save US$6 billion and adapt to "changing market conditions". Similarly, Swedish build-it-yourself furniture chain Ikea plans to cut 7,500 positions over the next two years, representing about 5% of the company's global workforce.

For telcos to get the most out of artificial intelligence (AI), they must not only find the necessary technical skills but also ensure that the entire company understands the value of the technology. My last blog focused on how AI augmentation is the future for telcos because it not only allows them to deliver superior customer experience in an increasingly competitive marketplace, but also helps them cut costs, remain competitive and launch new services across complex ecosystems, from autonomous cars and fleet management to healthcare and beyond. I concluded that the biggest challenge doesn't seem to be the implementation of the technology but the upskilling and retraining of human employees. According to a study from Oracle and Future Workplace, 72% of human resources executives surveyed said their organisations do not provide any AI training programme. Now, that study might not be telco-specific, but it certainly illustrates the challenges that AI brings when implementing it in a business.

Netcore, a global Marketing Technology Company that offers solutions for enterprises Digital Marketing, organized a corporate training programme on Artificial Intelligence (AI) and Machine Learning (ML) for marketers to understand how to implement new age technology in their marketing campaigns. Marketers today have moved from a'batch & blast' approach to a behavior-based approach in their marketing automation strategy. By deploying analytics tools, marketers are able to set smart triggers based on various criteria such as RFM (Recency, Frequency, & Monetary analysis) combined with demographic & category affinity. With the advent of Artificial Intelligence, these professionals can derive greater value from their strategies with hyper-personalize campaigns aimed at creating 1:1 customer experiences. These technologies also enable a multi-fold increase in the Customer Life Cycle as AI allows one to harness data, and analyze it to generate insights in response to unpredictable situations, and that too in real time.