Is the robot 反乱 about to begin? OpenAI and Meta are 始める，決める to 解放（する） AI models 有能な of 推論する／理由ing and planning - 批判的な steps に向かって 'superhuman cognition'
- OpenAI and Meta could soon 解放（する） the new ChatGPT-5 and Llama 3? models?
- These AI could be made much more powerful with the ability to 計画（する） and 推論する／理由?
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As far as AI has come in the last few years there are still a few things that machines can't do 同様に as humans.
However, all of that might soon change as OpenAI and Meta are both 報告（する）／憶測d to be on the brink of 解放（する）ing AIs 有能な of 推論する／理由ing and planning.
Leaders of both companies 示唆する that the 最新の 見解／翻訳／版s of their AI models are coming soon and will be a lot more powerful.
によれば their 報告（する）／憶測s, ChatGPT-5 and Llama-3 will not just 生成する text but start to do something that looks a lot more like thinking.
Joelle Pineau, 副／悪徳行為-大統領，／社長 of AI 研究 at Meta says: 'We are hard at work in 人物／姿／数字ing out how to get these models not just to talk, but 現実に to 推論する／理由, to 計画（する）... to have memory.'
Meta, Facebook's parent company, has 確認するd that it will soon 解放（する） the next 世代 of its AI model which could have the capacity to 推論する／理由 and 計画（する）?
Meta told MailOnline that the company would soon begin 株ing 早期に 見解／翻訳／版s of its Llama 3 model と一緒に a 十分な collection of models 予定 to 解放（する） throughout 2024.
OpenAI has 計画（する）s to 解放（する） GPT-5 'soon', (n)役員／(a)執行力のあるs told the?財政上の Times.?
現在／一般に, apps like ChatGPT use AIs called Large Language Models (LLMs) to 予報する what words should come next in a 宣告，判決.?
By training these LLMs on lots of data, the AI gets so good at 予報するing strings of words that it starts to sound like an intelligent, thinking スパイ／執行官.?
However, Yann LeCun, Meta's 長，指導者 AI scientist, says that even the best AI can still 'make stupid mistakes'.
Speaking at a Meta event in London this Tuesday, Mr LeCun said that AIs 現在／一般に 'produce one word after the other really without thinking and planning.'
He 追加するd that 追加するing the ability to 推論する／理由 would 許す AI to search through possible answers, 計画（する） out its 活動／戦闘s, and create a 'mental model of what the 影響 of [its] 活動／戦闘s are going to be.'
Brad Lightcap, OpenAI's 長，指導者 operating officer, says: 'I think we're just starting to scratch the surface on the ability that these models have to 推論する／理由.
Yann LeCun (pictured), Meta 長，率いる of AI 研究, says that 現在の AI makes simple mistakes because they cannot 計画（する） ahead. This is something that the next 世代 of models may solve
OpenAI's CEO Sam Altman (pictured) has brought AI chatbots into the mainstream. But as intelligent as they appear 専門家s 疑問 that any AI will become sentient anytime soon?
'We're going to start to see AI that can take on more コンビナート／複合体 仕事s in a more sophisticated way.
'I think over time... we'll see the models go に向かって longer, 肉親，親類d of more コンビナート／複合体 仕事s, and that 暗黙に 要求するs the 改良 in their ability to 推論する／理由.'?
Mr LeCun, 一方／合間, says that Meta is working on new AI 'スパイ／執行官s' that will be able to 計画（する） out and 調書をとる／予約する every step of a 旅行 from Paris to New York.?
These changes would be a big step 今後 for the 力／強力にする of AI models, and could even be a step closer to the 創造 of 人工的な general 知能 (AGI).??
AGI, seen by many as the 結局の goal of AI 研究, 目的（とする）s to build machine learning systems that reach a human level of cognition across any 仕事.
To 達成する this, AI would need to be able to 完全にする コンビナート／複合体 sequences of 仕事s and 予報する what their 活動／戦闘s would be.??
Not all 研究員s are 確信して this can be 達成するd, although Elon Musk recently 予報するd that AI would become more intelligent than the smartest human by the end of next year.
HOW ARTIFICIAL INTELLIGENCES LEARN USING NEURAL NETWORKS
AI systems rely on 人工的な neural 網状組織s (ANNs), which try to ふりをする the way the brain 作品 ーするために learn.
ANNs can be trained to recognise patterns in （警察などへの）密告，告訴（状） - 含むing speech, text data, or visual images - and are the basis for a large number of the 開発s in AI over 最近の years.
従来の AI uses input to 'teach' an algorithm about a particular 支配する by feeding it 大規模な 量s of （警察などへの）密告，告訴（状）.???
AI systems rely on 人工的な neural 網状組織s (ANNs), which try to ふりをする the way the brain 作品 ーするために learn. ANNs can be trained to recognise patterns in （警察などへの）密告，告訴（状） - 含むing speech, text data, or visual images
Practical 使用／適用s 含む Google's language translation services, Facebook's facial 承認 ソフトウェア and Snapchat's image alter ing live filters.
The 過程 of inputting this data can be 極端に time 消費するing, and is 限られた／立憲的な to one type of knowledge.?
A new 産む／飼育する of ANNs called Adversarial Neural 網状組織s 炭坑，オーケストラ席s the wits of two AI bots against each other, which 許すs them to learn from each other.?
This approach is designed to 速度(を上げる） up the 過程 of learning, 同様に as 精製するing the 生産（高） created by AI systems.?
