A team of researchers at DeepMind develops an AI agent called DeepNash that can play the Stratego game at an expert level.
The Stratego game is a two-player board game and is difficult to master. The goal for each player in Stratego is to capture their opponent’s flag hidden among their initial 40 game pieces. Every game piece is marked with a power ranking. Higher-rank players defeat the lower-ranked players during the face-offs in Stratego. The players in Stratego cannot see the markings of the opponent’s game pieces until they are in face-offs.
DeepNash first learned to play the Stratego game against itself many times. Researchers at DeepMind came up with an algorithm based on game theory, which uses an optimal strategy for every move in the game. They have published and explained the entire work of DeepNash in the paper, ‘Mastering the game of Stratego with model-free multiagent reinforcement learning.’
Testing revealed that DeepNash achieved an 84% winning rate against the top expert human players on the Gravon games platform and became one of the top three players. Gravon is a virtual world that allows users to play board and card games together. Researchers did not inform the players on Gravon that they were playing against a computer.
Google has announced that it has shut down Duplex on the Web, a service that enables Google Assistant to automate specific user tasks for site visitors.
According to the Google support page, Duplex on the Web is “deprecated” and, as of this month, will no longer be in use. Any automation features facilitated by Duplex on the Web will not be available any longer, says the page.
“As we continue to enhance the Duplex experience, we are responding to feedback from developers and users about how to make it even better,” a Google spokesperson said.
“By the end of this year, we will turn down Duplex on the Web and focus fully on making AI advancements to the Duplex voice technology that assists people most every day,” they added.
The company launched Duplex on the Web at its 2018 Google I/O developer conference. It enables Google Assistant to perform different site actions. These actions are performed under the full supervision of the user, who can terminate the process and take back control at any time.
There has been a lot of hype around generative AI since the beginning of 2022. Social media platforms such as Reddit and Twitter are full of images created through the generative machine learning models such as Stable Diffusion and DALL-E. Startups building products through generative models are attracting massive funding despite the market downturn. And large tech companies have started to integrate generative models into their mainstream products.
The concept of generative AI is not new. With a few exceptions, most of the advancements we are witnessing today have existed for several years. However, the emergence of several trends has made it possible to make the most out of the generative models and bring them to everyday applications. The field still has several challenges to overcome, but there is no doubt that the generative AI market is bound to grow in 2023.
Advancements in Generative AI
Generative AI became famous in 2014 with the rise of generative adversarial networks (GANs), which is a type of deep learning architecture that can create realistic images, for example, of faces from noise maps. Scientists later created other versions of GANs to perform different tasks, like converting the style of one image to another. GANs and the variational autoencoders (VAE), another deep learning architecture, later welcomed the era of deepfakes, which is an AI technique that modifies videos and images to swap one person’s face for another.
The year 2017 ushered in the transformer, a deep learning architecture that underlies large language models (LLMs) such as GPT-3, LaMDA, and Gopher. The transformer generates text, software code, and even protein structures. A variation of the transformer, called the “vision transformer,” is also utilized for visual tasks such as image classification. A previous version of OpenAI’s DALL-E used the transformer to create images from text.
A technique introduced by OpenAI in 2021, called Contrastive Language-Image Pre-training (CLIP), became crucial in text-to-image generators. CLIP is effective at learning shared embeddings between text and images by learning from image-caption pairs collected from the internet. CLIP and diffusion (another deep learning technique used for generating images from noise) were utilized in DALLE-2 to create high-resolution images with stunning quality and detail.
As we moved toward 2022, larger models, better algorithms, and more extensive datasets helped improve the output of generative models, creating superior images, generating long stretches of (mostly) coherent text, and writing high-quality software code. Besides, several models became available for the general public to experiment with, making them popular among the masses. In September, OpenAI’s DALL-E became available to everyone. The company removed the waitlist to allow open access to its text-to-image generator DALL-E 2.
“More than 1.5 million users are now actively creating over 2 million images a day with DALL-E, from artists and creative directors to authors and architects, with about 100,000 users sharing their creations and feedback in our Discord community,” said an OpenAI spokesperson, elaborating on the popularity of their generative AI tool.
Newer Applications
Generative models were first released as systems that could work with big chunks of creative work. GANs became popular for generating complete images with significantly less input. LLMs like GPT-3 were in the spotlight for writing full articles.
But as the field evolved, it has become evident that generative AI models are pretty unreliable when left to their own whim. Many scientists believe that current deep learning models lack some of the essential components of intelligence, no matter how large they are, which makes them prone to committing unpredictable mistakes. Recently, Meta introduced a new large language model ‘Galactica’ to generate original academic papers with simple prompts. But as more and more people reported it to be full of “statistical nonsense” and that it was developing “wrong” content, the website withdrew the option for people to experiment with.
Product teams are finding that generative models perform best when implemented in ways that facilitate greater user control. The past year witnessed several products that use generative models in clever, human-centric ways. For instance, Copy AI, a tool that uses GPT-3 to create blog posts, has an interactive interface where the writer and the LLM create the outline of the article and build it up together. Applications developed with DALL-E 2 and Stable Diffusion also facilitate user control with features that allow for regenerating, configuring, or editing the output of the generative AI model.
As the principal scientist at Google Research, Douglas Eck, said at a recent AI conference, “It is no longer about a generative AI model that creates a realistic picture. It is about making something that you created yourself. Technology should serve our need for agency and creative control over our actions.”
Conclusion
The generative AI industry still has many challenges to overcome, including copyright and ethical complications. Nevertheless, it is interesting to see the generative AI field thrive. As major generative AI models become accessible to the general public, it is obvious that everyone is benefiting from these powerful tools. Moreover, big companies like Microsoft are making the most out of their exclusive access to OpenAI’s technology, cloud infrastructure, and the huge market for creativity tools to bring generative models to its users.
However, down the road, the real potential of generative AI might manifest itself in unexpected markets. Who knows, perhaps generative AI will give birth to a new era of applications that we have never thought of before.
Reddit, the American social news and content aggregator, hits an all-time high in minting NFT avatars by having over 2,55,000 minted in a day, approximately 55,000 more than the previous record set on August 30-31.
In July, Reddit launched its limited-edition NFT avatars, created by independent artists. Initially, Reddit evaded using cryptocurrency to pay for avatar purchases and referred to them as digital “collectibles” instead of NFTs. Thus, the collection was generally viewed as a strategy to encourage the widespread adoption of blockchain technology.
Within the next few months, Reddit’s NFT avatar trading volume touched US$1.5 million, as per a Dune Analytics and Polygon report. The surge in avatar trading accounted for more than a third of the total volume (US$4.1 million), while the daily sales of digital collectibles also skyrocketed to 3,780.
On secondary NFT marketplaces like OpenSea, some of the costly Reddit NFTs have sold for over $300, while the platform’s own marketplace only reports values of approximately $50.
Researchers from the Kyoto University Institute for the Future of Human and Society have shown AI’s capability to develop literary art like Haiku, a Japanese poetic form.
A study led by Yoshiyuki Udea, one of the researchers at Kyoto University, compared AI-generated Haiku without human intervention, also known as the ‘human out of the loop’ or HOTL, with an opposing method known as ‘human in the loop’ or HITL.
The research involved 385 participants who evaluated 40 Haiku poems comprising 20 each of HITL and HOTL and 40 other poems composed by professional Haiku writers. Ueda said, “it was interesting that the evaluators found it difficult to differentiate between human-generated Haiku and AI-generated Haiku.”
From the result, HITL Haiku received more praise for their poetic capabilities, whereas HOTL and human-generated Haiku had similar scores. However, researchers witnessed algorithm aversion among the evaluators. They were not supposed to be biased but became influenced by reverse psychology. In other words, evaluators tended to give lower scores to those they felt were AI-generated Haiku.
According to the researchers, the capability of AI in the field of Haiku creation is an essential and initial step to collaborating with humans to produce more creative work.
According to the user safety report of October 2022, WhatsApp has banned 23,24000 Indian accounts, from which 811000 accounts were proactively banned before any reports from the users.
As per the September month report, WhatsApp banned about 26.85 lakhs of Indian accounts, which is more than the number of Indian accounts blocked in October 2022.
The report of October 2022 revealed that WhatsApp had received a total number of 701 grievances, out of which WhatsApp addressed only 34 grievances. Only the ban appeal grievances were approved by WhatsApp, which had 550 ban reports, and only 33 accounts were banned. Other grievances in the report, such as account support, additional support, product support, and safety, were hardly noticed.
Some of the grievances in the report were reviewed but have not been included as actioned due to the following reasons:
the user needs assistance from WhatsApp to access their accounts
the reported account does not violate WhatsApp’s Terms of Service or the laws of India
the user is writing to WhatsApp to offer feedback regarding its service
the user needs assistance to use one of our features
the user requests restoration of a banned account is denied
Safety-related grievances in the report are issues about abuse or harmful behavior on the platform. For such grievances, WhatsApp responds to the user, guiding them to report the complaint with in-app reporting.
The Department of Telecommunications (DoT) has recently sent a letter to telecom companies like Airtel, Reliance Jio, VI, and more to prevent installing C-band 5G base stations within a 2.1km range of Indian airports.
According to DoT, C-band 5G base stations can create problems with the aircraft’s radio altimeters during takeoff and landing. As per the letter, telecom service providers (ISP) are advised that in the area of 2100 meters from both ends of the runway and 910 meters from the center line of the runway of Indian Airports must have no 5G base stations.
The letter also mentioned that for the base station, nodal, or repeater installed in the border of 540 meters surrounding the area, the maximum power should be limited to 58 dBm/MHz in 3300-3760 MHz.
Telecom firm like Airtel has installed 5G stations at airports in Nagpur, New Delhi, Guwahati, Pune, and Banglore. In comparison, Jio has installed 5G base stations in the Delhi NCR area.
As per DoT, the Ministry of Civil Aviation has offered the buffer and the safety zone sketch and has also requested to ensure mitigation during the implementation of C-band 5G base stations in and around airport areas for aircraft safety concerns.
The DRDO Young Scientist Lab – Artificial Intelligence (DYSL-AI) has issued an advertisement for Junior Research Fellows (JRF) for the engagement of meritorious Indian nationals who desire to pursue AI-related research.
The junior research fellowship has three vacancies. Graduates in professional courses such as B.E/B. Tech in the first division with GATE/NET are eligible. Candidates with a postgraduate degree in basic sciences or professional studies like M.E/M. Tech in the first division can also apply.
Candidates will work initially for the first two years as JRF. They will subsequently be promoted as a senior research fellow (SRF) for the remaining two or three years. It will be subject to satisfactory performance, which will be assessed annually as per DRDO rules. The last date to apply for the fellowship is December 31, 2022.
A stipend of ₹31000 per month plus house rent allowance (HRA) as applicable (at present, 27%). Hence, the total payment will be ₹39,370. The upper age limit to apply is 28 years as on the interview date.
DYSL-AI comprises young scientists working towards research and development in artificial intelligence. DRDO Young Scientist Artificial Intelligence (DYSL-AI) is a pioneer of research in artificial intelligence. The lab has associations with various organizations such as IITs, IISc Bangalore, IIITs, and other leading academic institutions.
Lensa AI, the image editing app, has recently launched its new feature that uses AI to create customized avatars for android and iOS devices.
Launched in 2018, Lensa AI has a wide range of features that allows users to improve their facial touch in images, perfect the facial imperfections with a variety of cool tools, replace or blur out the background of images with a single touch, apply unique filters and special effects to level up your photos, and more.
To access all the features of Lensa AI, users must pay an annual subscription fee of ₹2499. They can also get a monthly and weekly subscription plan for ₹419 and ₹249, respectively.
Users must be at least 18 years of age to use Lensa AI to create customized avatars. They must upload 10 to 20 selfies to Lensa’s servers to create avatars. As per Lensa AI, all the pictures or images uploaded to Lensa’s servers will be deleted immediately as the avatars are ready.
Lensa AI is a great app that can give your images or selfies a new look. However, many of its features are limited to paid users only. Free users can also access various capabilities of the Lensa AI app. If you are looking for a modern, AI-enabled photo and video editor, Lensa AI is a better option for you.
In downtown Vancouver, when customers ordered pizza on Canadian sidewalks, they were greeted by Angie, Hugo, and Raja, four-wheeler food delivery robots with eyelike lights. The robots traveled to the customers who used their unique codes to access their lids and retrieve their orders.
However, the advancement has yet to be welcomed completely. Serving robots have been a debatable value proposition arising from Uber’s 2020 acquisition of Postmates. These robots gained much attention during the labor crunch, climate change, and a slim restaurant margin.
Delivery robots have also been outlawed in certain cities, including Toronto, because they pose a risk to the elderly, children, and those with poor vision or movement. Robots are not welcome in bike lanes, where cyclists already complain about e-scooters. There are also concerns that autonomous robots or ones operated by personnel from outside would eliminate work for couriers.
Prabhjot Gill, McKinsey & Co associate, said, “They’re drawing a lot of attention from pedestrians while they’re out on the sidewalk because they’re not seeing them that often and people are excited to see them, but as usage continues to increase, this can cause a lot of congestion on already narrow sidewalks.”
The chief executive of Serve, Ali Kashani, who was born and raised in Vancouver, views the criticism as an inevitable aspect of innovation. He has made sure that his robots chime and flash their lights to warn people to allay their fears. Besides, they also have emergency braking, automatic crash prevention, and vehicle collision avoidance.
