Alibaba Deepens Push Into AI Smart Glasses With Hong Kong’s RayNeo
A new partnership will see Alibaba Cloud develop customized AI models for RayNeo products, the companies say
Alibaba Group Holding is pushing further into the expanding market for artificial intelligence (AI) hardware through a new partnership with Hong Kong-based augmented reality (AR) glasses maker RayNeo.
Under the deal, the cloud computing and AI unit of Alibaba will provide exclusive technology support for RayNeo’s products through its Qwen large language models (LLMs), the companies said on Thursday. LLMs are the technology underpinning generative AI services such as OpenAI’s ChatGPT.
“This partnership represents a new application of the Qwen LLM in the field of smart glasses,” said Zhou Jingren, chief technology officer at Alibaba Cloud. It also marks the first in-depth collaboration between an LLM developer and an AI glasses manufacturer in China, according to Alibaba Cloud. Alibaba owns the South China Morning Post.
Smart glasses, which are lighter and slimmer than AR and virtual reality headsets, have seen a surge in fresh interest stemming from new capabilities introduced by generative AI.
More on the RayNeo | Alibaba AI smart-glasses on SCMP
AI Is Making The Existing Workforce 'Stronger' | Matt Wood, PwC Innovation
As companies evolve in the artificial intelligence era, PwC Global and US commercial technology and innovation officer Matt Wood joins Wealth Host Brad Smith to discuss what AI means for the organizations employing it, especially as the use of AI service agents rises in popularity. "AI, as we see it today, is probably the single largest shift in how we're going to interact with data and information and each other, probably since the advent of the very, very earliest internet," Wood says.
He adds that organizations that invested "in the early internet 30 years ago went on to experience pretty tremendous growth in the intervening couple of decades, and it's my guess that organizations that are investing in generative AI today are going to experience the same, if not more, growth over the next ten, 20, 30 years going forward."
"Whilst there is some angst around what that means to the workforce, at least what we've seen at PwC is that organizations that are applying generative AI in a way, which is responsible, it actually makes the intelligence and the expertise of their existing workforce stronger. It doesn't replace individuals; it augments their abilities and their expertise and allows them to deliver much higher leverage for the organization."
Generative AI Funding Reached New Heights With $56 Billion Raised In 2024
If there was any doubt, the generative AI bubble did not burst in 2024.
Investments in generative AI, which encompasses a range of AI-powered apps, tools, and services to generate text, images, videos, speech, music, and more, reached new heights last year. According to data from financial tracker PitchBook compiled for TechCrunch, generative AI companies worldwide raised $56 billion from VCs in 2024 across 885 deals.
That raw cash total is a new record for the segment. It’s up 192% from 2023, when investors poured $29.1 billion into generative AI startups across 691 deals.
“We aren’t seeing a slowdown in generative AI funding, as big names like OpenAI, Anthropic, and xAI continue to secure major raises and release new, competitive products,” said Ali Javaheri, an emerging technology analyst at PitchBook, in an interview.
Deal value in Q4 2024 soared to $31.1 billion with the closure of mammoth rounds like Databricks’ $10 billion Series J, xAI’s $6 billion Series C, Anthropic’s $4 billion strategic investment from Amazon, and OpenAI’s $6.6 billion round.
Mergers and acquisitions were a small share of generative AI investments in 2024: $951 million, per PitchBook data. To be clear, that’s exclusive of the various “acqui-hire” deals executed by Google, Microsoft, and Amazon. Google reportedly paid $2.7 billion to hire much of chatbot startup Character AI‘s staff and license its technology, while Microsoft is said to have spent $650 million licensing Inflection‘s AI models and hiring its CEO, Mustafa Suleyman.
More on GenAI’s record-breaking fundraising push on Tech Crunch
United Nations Security Council Meeting On Artificial Intelligence (AI)
The United Nations Security Council debates use of Artificial Intelligence in conflicts, and hears calls for a UN Framework to avoid fragmented governance.
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AI Hit 'Peak Data.' Google Researchers Think They Found A Solution
OpenAI cofounder Ilya Sutskever announced something at a recent conference that should have had the AI industry trembling with fear. "We've achieved peak data and there'll be no more," he intoned during a speech at the annual Neurips event in December.
All the useful data on the internet has already been used to train AI models. This process, known as pre-training, produced many recent generative AI gains, including ChatGPT. Improvements have slowed, though, and Sutskever said this era "will unquestionably end." That's a frightening prospect because trillions of dollars in stock market value and AI investment are riding on models continuing to get better.
Yet, most AI experts don't seem that worried. Why?
Inference-time compute
There may be a way to get around this data wall. It's related to a relatively new technique that helps AI models "think" through challenging tasks for longer.
The approach, called test-time or inference-time compute, slices queries into smaller tasks, turning each into a new prompt that the model tackles. Each step requires running a new request, which is known as the inference stage in AI. This produces a chain of reasoning in which each part of the problem is tackled. The model doesn't move on to the next stage until it gets each part right and ultimately comes up with a better final response.
OpenAI released a model called o1 in September that uses inference-time compute. That was followed swiftly by Google and Chinese AI lab DeepSeek, which rolled out similar "reasoning" models.
More on Inference-time compute models on Business Insider
The Construction Industry Has A CO2 Problem And Concrete.ai Aims To Fix It
Mathieu Bauchy, Cofounder of Concrete.AI, knows there are areas of improvement within the construction industry, especially when it comes to the very precarious material called concrete.
However, with carefully applied AI models, Bauchy and his team have created a product for concrete producers that can help reduce CO2 emissions and cut production costs.
AI Agents In 2025: What Enterprise Leaders Need To Know
"2025 will be the year of the AI agent." Wait — didn’t we already say that in 2023? Back then, I talked about chaining AI models in my podcast. The excitement around AI was huge, and by 2024, many companies rushed to try generative AI, with some even using chained models.
But many of these projects failed to scale. Why? Because they were test projects that were not integrated into the system infrastructure or were missing guardrails and quality controls. This will change in 2025, but the product challenges will remain the same. To see what AI agents can do in 2025, let’s consider a simple example: an email-answering tool. Imagine a system that drafts replies to emails automatically. This example shows the opportunities and challenges businesses face with AI agents.
Why GPT Wrappers Are Not Enterprise AI
The simplest way to build an email-answering tool is with a GPT wrapper. I saw many of these in 2024. These are basic setups where you connect AI to a small interface. For our use case, this means getting a ChatGPT API key, writing some code to take an email as input, adding a prompt telling the AI what to do, and displaying the response in a clean interface.
System Prompt: Answer as if you were Lutz. Lutz always ends his messages with "Cheers!"
Input: Hi Lutz, you are invited for dinner on Thursday. Can you come? Cheers, Tim.
Output: Thanks, Tim! Let me check my schedule and I’ll get back to you soon. Cheers!
Even in this simple example, several key challenges emerge for enterprise AI today:
No System Integration: The tool can’t check my calendar to see if I’m free.
No Context: It doesn’t know if I like Tim or avoid these types of events.
No Security: What if the email asks for private details, like my social security number?
No Guardrails: How would it handle a controversial question, like asking for political views?
No User Control: How much input does the user have in shaping the AI’s response?
Hallucinations: AI sometimes makes things up, as the warnings on ChatGPT pages constantly remind us: “ChatGPT can make mistakes.”
Large language models are excellent at tasks like summarization or acting as interfaces, but alone they are not enough …
More on what enterprise leaders need to know about AI Agents in 2025
Max Tegmark: Will AI Surpass Human Intelligence? | Into The Impossible
Will AI ever surpass human intelligence, discover new laws of physics, and solve the greatest mysteries of our universe? This week on Into the Impossible, I explore the potential and dangers of artificial intelligence with none other than Max Tegmark!
Max Tegmark is a renowned physicist and machine learning expert who dedicated his career to uncovering the mathematical fabric of reality, proposing that our universe itself might be a vast mathematical structure and that we could be living in a multiverse of endless possibilities.
His work goes beyond physics to tackle the transformative power and ethical challenges of artificial intelligence, an area where he believes humanity must tread carefully. In the second part of our fascinating interview, we discuss the development of AI, the impact it will have on science, and our role in all of this.
Tune in to discover if AI will ever surpass human intelligence! Check out the first part of our interview, where we discuss his mathematical universe hypothesis, the search for extraterrestrial life, and AI’s role in science.
Thats all for today, however new advancements, investments, and partnerships are happening as you read this. AI is moving fast, subscribe today to stay informed.