Google's Race for AI Dominance: Battling ChatGPT and Bing Chat

Google's pursuit of AI supremacy faces challenges as it aims to keep up with rivals like ChatGPT and Microsoft Bing Chat. Despite introducing Google Bard as a Large Language Model (LLM) chatbot, the platform has struggled to resonate with a broader audience due to its belated entry and limited capabilities.

In a strategic move, Google appears ready to leverage the knowledge gained from Bard and channel it into enhancing its primary digital co-pilot, Google Assistant. An internal email shared with Axios revealed plans for a significant overhaul of the Assistant, delving into the potential of generative AI and catering to the growing demand for assistive conversational technology.

With an estimated 3.1 billion voice searches made monthly in the U.S. alone, the upgraded Assistant has the potential to revolutionize AI adoption at home, allowing for more engaging interactions beyond simple prompt responses. Despite facing competition from AI-backed smart assistants like Josh.ai, Google Assistant's wide availability on various devices positions it for widespread adoption.

While Google perceives the Assistant overhaul as a tremendous opportunity, some analysts question whether it might be overkill, given that the majority of digital assistant requests involve basic tasks like setting timers and playing music. This raises concerns about the fate of Bard, which could potentially be overshadowed by the revamped Assistant.

Nonetheless, Google's commitment to embracing generative AI signifies a bold step towards staying at the forefront of the AI landscape. As the company explores new possibilities and works to create a supercharged Assistant powered by the latest LLM technology, the future of AI interactions holds promise and potential for exciting advancements in user experiences.

🚀 Recent AI Feats 🚀

1. AI to See Through Pitch Dark: Engineers at Purdue University have developed a patent-pending method called HADAR (heat-assisted detection and ranging), which combines thermal physics, infrared imaging, and machine learning to enable AI to see through darkness with the same clarity as in daylight. Unlike traditional thermal imaging, HADAR recovers texture, depth, and physical attributes of objects in a scene, overcoming the "ghosting effect" that limits machine perception using heat radiation. The technology has potential applications in automated vehicles, robots, agriculture, defense, geosciences, healthcare, and wildlife monitoring. Further improvements are underway to reduce the sensor's size and increase data collection speed to make it viable for autonomous vehicles and robots.

2. GPT-3 Reasons as well as a College Student: Researchers at UCLA have found that GPT-3, the language model by OpenAI, performs at a level similar to college students in solving reasoning problems typically found in intelligence and standardized tests. The study raises the question of whether GPT-3's reasoning capabilities stem from mimicking human reasoning or if it employs a fundamentally new cognitive process. However, without access to GPT-3's internal workings, researchers cannot determine how its reasoning functions. While GPT-3 shows promise in analogy problem-solving, it still falls short in understanding physical space and practical problem-solving. The researchers are interested in exploring whether language learning models like GPT-3 are genuinely thinking like humans or adopting an entirely novel form of artificial intelligence.

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